Connectedness

What does leadership look like? By Vaclav Havel

2010-06-08T16:23:00.007-04:00

After reading my recent response to her question, "What does leadership look like in a healthy network," Claire Reinelt referred me to Vaclav Havel, leader of the Velvet Revolution (which brought a peaceful end to Communist rule in Czechoslovakia 20 years ago). In Fall 2009, the International Leadership Association (ILA) held its annual conference in Prague and awarded its Distinguished Leader Award to Havel. He accepted the award and welcomed the conference with these words about leadership (translated from Czech) :

Ladies and gentlemen, allow me to greet your conference most warmly and thank you for the award I am to receive from you. I think it is splendid that this conference is taking place in Prague -- not simply because it honors and publicizes our capital city, but also because of the topic of your conference at a time when are truly in need of good leaders. Your conference can be an asset to its host country and provide some lessons.

You have approached me as a leader although I don't know whether I am a particularly typical one. And I am somewhat reticent about being labeled one. But if I try to step back from myself and reflect on this topic, then I do have after all one particular insight to share, namely, that people don't become central persons by their own decision; it is life that lures them and creates them. It doesn't require any particular leadership habits or style. A leader isn't someone who shouts or arouses fear in others, but rather someone that people need to have near them and feel at their backs.

I have one personal recollection. At a certain moment during our peaceful revolution, I was already very tired and exhausted from all the endless speculations, decisions, speech-writing and thinking up new things, and so I escaped for a couple of days to a secret location -- a friend's studio -- where I reflected on my coming speeches and tried to relax. Interestingly, I suddenly started to be missed at the Civic Forum, which was then the focus of all the revolutionary events. I was missed not because there was a specific job or task that I had to do without fail or one that I and only I could do. There was nothing that could not be dealt with without me, and yet I was missed. I was missed as a special kind of background support, the sort that we take into account and that we think about, one that in some way helps us to act and not become confused. Without my having realized it, or desired it, it strikes me that in that sense I was able to play the role of a central figure. I find it amazing, because I am the last person to consider myself to have charisma. However, since I have been invited to talk on this topic, I thought I would share this experience of mine with you.

Apart from all other abilities and skills, leaders should also have trust in their coworkers. They should radiate calm, and they should truly be a background support that others can sense, one that is important to them and gives them energy.

Thank you for your attention. I wish your conference every success.

A video of Havel's speech is here. Another transcription of the speech is hosted by ILA here.

Compare Havel's remarks to Verse 17 of the Tao Te Ching (expanding on the passage I quoted last time):

When the Master governs, the people
Are hardly aware that he exists.
Next best is a leader who is loved.
Next, one who is feared.
The worst is one who is despised.

If you don't trust the people,
you make them untrustworthy.

The Master doesn't talk, he acts.
When his work is done,
The people say, "Amazing:
We did it, all by ourselves!"
--Stephen Mitchell (trans 1988)

Thanks, Claire, for illuminating my Taoist quotes on leadership with such a timely example.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2010 by Connective Associates LLC except where otherwise noted.

What does leadership look like?

2010-06-02T14:17:00.006-04:00

The Leadership Learning Community is hosting an interesting conversation on network leadership. As part of that dialogue, Claire Reinelt put to me the question, "What does leadership look like in a healthy network?"

In response, I turn to The Tao Te Ching by Lao Tsu. This ancient Chinese book of wisdom has inspired many translators to describe leaders and leadership of healthy networks. A few examples are below.

The best leader is one whose existence is barely known by the people.
True Persons do not offer words lightly.
When their task is accomplished and their work is completed,
The people say, "It happened to us naturally."

--Tolbert McCarroll (trans 1982)

When the Master governs, the people are hardly aware that he exists.
The Master doesn't talk, he acts.
When his work is done, the people say,
"Amazing: we did it all by ourselves!"

--Stephen Mitchell (trans 1988)

The "very highest" by those below is just known to exist.
He takes his time, oh, as he weighs his words carefully.
And, when success is had and the task accomplished,
The common folk all say, "We just live naturally."

--Richard John Lynn (trans 1999)

To know Tao alone without trace of your own existence is the highest.
The great ruler speaks little and his words are priceless.
He works without self-interest and leaves no trace.
When all is finished, the people say, "It happened by itself."

--Jonathan Star (trans 2001)

The very highest is barely known by men.
When actions are performed
Without unnecessary speech,
People say, "We did it!"

--Gia-Fu Feng (trans 1972)

BTW, this is not the first time the Tao Te Ching has graced these pages.

See here for Taoist perspective on the spread of information.
See here and here for Taoist perspective on naming and organizing things.

Organizational and network leadership

2010-05-26T16:38:00.004-04:00

Many thanks to the Leadership Learning Community for honoring me with the monthly member spotlight in their newsletter published today.

The same newsletter features Claire Reinelt's article, "How is network leadership different from organizational leadership." She shares a chart from the Monitor Institute that breaks it down like so:

Organizational Leadership	Network Leadership
Position, authority	Role, behavior
Individual	Collective
Control	Facilitation
Directive	Emergent
Transactional	Relational, connected
Top-down	Bottom-up
Action-oriented	Process-oriented

Here's what is meaningful to me in this table:

Network leadership emerges and dissolves in accordance with its environment (emergent facilitation).
Organizational leadership sustains itself with a force distinct from its environment (directive control).

Web science, Webwhompers

2009-12-14T11:56:00.004-05:00

I have just unveiled Webwhompers, which bears the fruit of four years of my teaching Web science at Boston University. The site features a few interests of mine:

A solid layman's introduction to Web science, focusing on the intersection of mathematics, sociology, and the Web as it is used and built by regular people. It is all presented as an online textbook you can read here.
A case study in educational methodology. Unlike the online textbook, which is meant to be read, the rest of Webwhompers is meant to be experienced. It provides the online portion of my answer to the question, "What can 70 non-technical college students do together in 12 weeks that will result in their learning as much as possible about the Web?"

The course mission statement puts it this way:

Technology is often created by "experts" and then used by "regular people." Webwhompers celebrates the "Web builder": a regular person who creates his own Web technology.

Sometimes it helps to distinguish between "regular people" who use technology and "experts" who create technology. For example, a regular person might want a home stereo; he pays experts to create hi-fi technology for him. In other cases, regular people create technology without even considering asking for expert help—for example, making a snowball.

Much of the Web technology that regular people want is within their power to create, just like a snowball. Webwhompers seeks to unleash the technical creativity of the regular person: By highlighting Web building resources, by bringing together aspiring Web builders, by providing expert guidance when necessary, and by encouraging regular people to try on the idea that they can create their own Web technology.

The course overview puts it this way:

Our course introduces Web science. It has no prerequisites and has been used by non-technical undergraduates at Boston University since 2006. Our curriculum is guided by the following passage adapted from "Web Science: An Interdisciplinary Approach to understanding the Web," by James Hendler, Nigel Shadbolt, Wendy Hall, and Tim Berners-Lee:

Web science, an emerging interdisciplinary field, takes the Web as its primary object of study. This study incorporates both the social interactions enabled by the Web's design and the applications that support them.
The Web is often studied at the micro scale, as an infrastructure of protocols, programming languages, and applications. However, it is the interaction of human beings creating, linking, and consuming information that generates the Web's behavior as emergent properties at the macro scale. These properties often generate surprising properties that require new analytic methods to be understood.
For example, when Mosaic, the first popular Web browser, was released publicly in 1992, the number of users quickly grew by several orders of magnitude, with more than a million downloads in the first year. The wide deployment of Mosaic led to a need for a way to find relevant material on the growing Web, and thus search became an important application, and later an industry, in its own right. The enormous success of search engines has inevitably yielded techniques to game the algorithms (an unexpected result) to improve search rank, leading, in turn, to the development of better search technologies to defeat the gaming. More recent macro-scale examples include photo-sharing on Flickr, video-uploading on YouTube, and social-networking sites like mySpace and Facebook.
The essence of Web science is to understand how to design systems to produce the effects we want. The best we can do today is design and build in the micro, hoping for the best; but how do we know if we've built in the right functionality to ensure the desired macro-scale effects? How do we predict other side effects and the emergent properties of the macro? Further, as the success or failure of a particular Web technology may involve aspects of social interaction among users, understanding the Web requires more than a simple analysis of technological issues but also of the social dynamic of perhaps millions of users.
Given the breadth of the Web and its inherently multi-user (social) nature, its science is necessarily interdisciplinary, involving at least mathematics, computer science, sociology, psychology, and economics.

Four important themes of Web Science are

Micro: an individual acts
Macro: the world responds (or not) to an individual's action
Synthetic: something is created to produce a desired result
Analytic: laws are stated to explain observed phenomena

We focus on these themes as they apply to Web builders -- people who contribute links and other content to the Web:

	Synthetic	Analytic
Micro	An individual builds a Web site to produce a desired result.	(We do not speak to this quadrant.)
Macro	"The world" builds a Web site to produce a desired result.	Laws are stated to explain large-scale Web phenomena.

Some Web builders consider themselves Web developers; others consider themselves bloggers; others merely post an occasional comment on someone else's blog or discussion forum. We say "Web builder" to encompass the full spectrum of people who contribute links and other content to the Web.

Our lab curriculum provides an informal hands-on approach to the task of building a Web site. Our Search and Share pages help Web builders leverage collectively engineered resources (such as WordPress). The formal chapters of the Study page (which you are now reading) explain large scale Web phenomena; they also explain the Amazon recommendation algorithm and the Google PageRank algorithm.

The sociology, psychology, and economics of this course follow Duncan Watts' Six Degrees, which we recommend as a narrative companion to our own material. Our complete suggested reading list is below.

Online safety

Protecting yourself from evildoers

“The Difference Between a Virus, Worm, and Trojan Horse” by Webopedia
"Secret geek A-Team hacks back, defends Web" by Joshua Davis, Wired, Nov 2008
"Thieves winning online war in your computer" by John Markoff, NY Times, Dec 2008

Privacy, trust, and ownership

"Google Knows All" by Sarah Elton of Macleans.ca.
"Wikipedia: What do they know; when do they know it, and when can we trust it?" by Susan Youngwood, Vermont Today, April 2007
Choosing a license by Creative Commons.

Networks

Basic mathematical foundations of networks:

Set Theory

Sets
Explicit Notation for Sets
Cardinality
Subsets
Venn Diagrams
Union and Intersection
Ordered Lists
Implicit Notation for Sets
Logical Expressions
Compound expressions with "or"
Compound expressions with "and"
Union and intersection defined formally
Similarity of Sets

Graph Theory

Graphs
Undirected and Directed
Neighborhood and Degree
Density and Average Degree
Paths
Paths in undirected graphs defined formally
Paths in directed graphs
Length
Distance

See also:

"Bow Tie" Structure of the WWW, by Chris Sherman, Information Today, May 22, 2000.
Six Degrees Chapter 2 (skim pp 48-55 & 62-68)

Network Dynamics

How randomness, homophily, and cumulative advantage shape the Web:

Network Dynamics

Limitations of traditional graph theory
Introduction to network dynamics
Three models of dynamic graphs
Random graphs
Demonstration of random graph dynamics
Random graph algorithm
Clusters and homophily
Triadic closure
Triadic closure algorithm
Hubs and cumulative advantage
Preferential attachment algorithm

See also:

"Is Justin Timberlake a product of cumulative advantage?" by Duncan Watts, The New York Times, April 2007
"Science Online: Too Much of a Good Thing?", NSF Press Release featuring sociologist James Evans, July 17, 2008.

Variables, Probability, and Scale-Free Networks

Understanding that the Web is a scale-free network requires some probability theory:

Variables and Probability

Variables in mathematics
Variables in algorithms
Random variables
Discrete vs. continuous variables
Probability distributions
Degree distributions

General discussion of scale-free networks:

Six Degrees Chapter 4, pp 101-114
From previous chapter on Network Dynamics
- Hubs and cumulative advantage
- Preferential attachment algorithm

Information and Computation

Applying fundamental concepts of computer science to the Web

Information and computation

Information, computation, and algorithms
Summation: an example of what computation is
HTML: an example of what computation is not
Computing distance, part one: Information diffusion
Computing distance, part two: Example
Computing distance, part three: Algorithm

Examples of information diffusion on the Web:

Social bookmarking in plain English by Common Craft
RSS:
- RSS in plain English by Common Craft
- What is RSS? by Software Garden
XML:
- Introduction to XML by Jan Egil Refsnes
- How can XML be used? by Jan Egil Refsnes

See also:

The Machine is Us/ing Us
Skim Six Degrees pp 135-139: "Is six a big or a small number?"

Collaborative Filtering

How to compute personalized recommendations:

Collaborative Filtering

"Expert opinions" without the experts
Delicious: example of CF
Bookmarks: content of Delicious
Tuples: content of CF
Bipartite graphs: structure of CF
Structural equivalence: computation of CF
Delicious: algorithmic summary
The four steps of collaborative filtering

The Long Tail

Niches and blockbusters in the world of Web commerce:

The Long Tail

Macro-analytic view of collaborative filtering
Power law revisited
Niches, megahits, and the neglected middle
Macro-analytic view of the long tail
Macro view of Web programming

See also:

The Long Tail, by Chris Anderson. Wired, October 2004.
Going Long, by John Cassidy. The New Yorker, July 2006.
Six Degrees Chapter 7, pp 207-215: Information Externalities & Market Externalities

Influence in Networks

How to compute the influence of a Web page:

Influence in Networks

Popularity, influence, and centrality
Introduction to PageRank
NetRank: a simplified version of PageRank
Normalization and convergence
The NetRank algorithm
Dividing by outdegree: the NR* formula
The PageRank formula
The damping factor: PageRank as probability

See also PageRank Explained by Phil Craven

Competition and Cooperation

What happens when Web builders seek to increase their influence?

Games: Competition and Cooperation

Dynamics of popularity and influence
PageRank competition
Doing the right thing
Mutually assured construction
Authority, reciprocity, reputation
Game theory
Winners' dilemma

Notable roles in living systems

2009-09-28T11:06:00.002-04:00

Measuring and mapping networks can help us understand a system holistically.

With that in mind, I paused a week ago to read an obituary in the NY Times: "Lawrence B. Slobodkin, Pioneering Ecologist, Dies at 81." Curious to see what had made Slobodkin a pioneer in his own systems-oriented field, I read on and discovered his most famous paper. Published in 1960 as "Community Structure, Population Control and Competition," the paper's four pages contain a grand overview of how terrestrial ecosystems work, and is still widely discussed today.

Slobodkin and his co-authors present these distinct roles in the terrestrial ecosystem:

fossil fuels
sunlight
producers (e.g., plants)
decomposers
herbivores
carnivores

They then tackle the overarching question: for each role above, what is the critical factor that limits its growth? For example, in which roles are peers competing for scarce resources, and in which roles are populations controlled not by scarce resources but by predation?

Somehow, I am convinced that these roles map in a meaningful way more recent natural systems such as the world economy or American healthcare. Which parts of these systems correspond to which of the above roles in the terrestrial biosphere? Any ideas, anyone?

One thing that surprised me about Slobodkin's map of the biosphere was its early and explicit inclusion of fossil fuels. This inclusion makes a lot more sense to me now that I am reading (coincidentally) Michael Pollan's Ominivore's Dilemma, which also speaks to a holistic view of the terrestrial biosphere. One of the darker themes of the book is that human desire for productivity leads people to feed plants with fossil fuels instead of sunlight.

The same day Slobodkin's obituary was published, the NY Times also featured this headline: "Emphasis on growth is called misguided," reporting a paper commissioned by Nicolas Sarkozy and written by a pair of Nobel-laureate economists.

It's a lot to absorb. But strikes me as relevant to those of us interested in metrics that pertain to well-being.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Interesting Webinar 9/14: Leadership for a New Era

2009-09-08T16:53:00.003-04:00

The wonderful Claire Reinelt recently shared this with me:

Leadership for a New Era

We invite ALL members of the leadership development community to join a free introductory webinar to the Leadership for a New Era (LNE) initiative on September 14th at 12:30 EDT (9:30 PDT). LNE is a collaborative learning initiative developed by the Leadership Learning Community (LLC), a nonprofit organization focused on connecting organizations and individuals in the leadership development field with a commitment to social equity. Through LNE we are establishing partnerships (such as these) to influence our current leadership development thinking and practice, and to promote a shift from a model of leadership focused on individual skills and attributes to a model of leadership that is inclusive, rooted in community, networked, and action-oriented. For additional information please visit the LNE website: http://leadershipforanewera.com

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Influence and social capital of 21st century leaders

2009-08-27T11:08:00.006-04:00

My previous post summarized "four fundamentals of networks" with special emphasis on the context of leadership. Today I'll take a closer look at the foundation of the four fundamentals: personal influence. This foundation is highlighted in the bottom two quadrants below, which share a network focus on influential positions and roles:
These two quadrants provide a good foundation for at least a couple reasons:

First, most of us naturally equate leadership with positions of personal influence. In their excellent article "Social Capital of Twenty-First Century Leaders," Dan Brass and David Krackhardt begin by saying, "Accomplishing work through others has always been the essence of leadership"; later in the chapter they simplify this to "Influence is the essence of leadership." As I summarized in this post, Brass and Krackhardt then describe how aspiring leaders can use social networks to gain as much influence as quickly as possible. (Their article really is outstanding, FYI.)

Second, centrality and structural holes--the network concepts underlying the highlighted two quadrants--are the two most intuitive notions of network structure. If you find "structural holes" less intuitive than "centrality," then just substitute "clustering" in place of "structural holes." Clustering refers to groups, structural holes to the gaps between groups: Just like foreground and background, they define each other in complementary partnership.

The topic of personal influence in social networks gets lots of attention. For example, this announcement crossed my desk last week: "'Influence is the future of media'. Influence is the hottest topic in marketing, advertising, media and social media today. Find out how to tap the power of influence." It's not too late to sign up for http://www.futureofinfluencesummit.com/.

Another view of influence and social networks crossed my desk a month ago: Duncan Watts, Columbia sociologist and principal research scientist for Yahoo, told Fast Company magazine his opinion of the idea that a subgroup of "influentials" is largely responsible for trend-setting: "It sort of sounds cool, but it's wonderfully persuasive only for as long as you don't think about it." Later in the article, Watts concludes: "If society is ready to embrace a trend, almost anyone can start one--and if it isn't, then almost no one can."

Are these views of influence hopelessly at odds? Perhaps not. As I explore that, I'll move to the top half of the four fundamentals of networks.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Four fundamentals of networks

2009-08-18T09:33:00.009-04:00

Claire Reinelt and I just contributed a chapter, "Social Networks," to appear in Political and Civic Leadership, edited by Richard Couto and produced by Sage Publications.

Political and Civic Leadership provides a comprehensive undergraduate-level overview of the field of leadership and includes 100 chapters in two volumes. We are happy to be included in an all-star cast of contributors (academics and practitioners of leadership); and we are also happy to be done!

Richard has structured the book as a reference, with each chapter standing on its own, so that readers can flip to a topic of interest (e.g., "decisions," "ethics," "globalization," "philanthropy") without having to read the preceding 500 pages. Nevertheless, there is an overarching structure to the 100 chapters that is not alphabetical. They are divided into these 11 thematic sections:

Introduction To Politics And Civic Leadership
Philosophy And Theories Of Political And Civic Leadership
Purposes Of Political And Civic Leadership
The Failure Of Politics
The Processes Of Political And Civic Leadership
The Institutions Of Political And Civic Leadership
The Contexts Of Public Leadership
The Psychology Of Public Leadership
The Tasks And Tools Of Political And Civic Leadership
The Competencies Of Public Leadership
Depictions Of Public Leadership

Our chapter will appear in Section 9: "The Tasks and Tools of Political and Civic Leadership."

The writing process helped us to deepen the foundations of our framework of four kinds of leadership networks. We considered three different perspectives, each of which describes a different set of four fundamentals of networks:

Kilduff and Tsai describe four orienting concepts of network thinking:

Embeddedness: How are organizations and behavior influenced by social relations?
Social Capital: What is the value of a person's connections to others?
Centrality: What is the influence of a person according to his position?
Structural Holes: Where are there gaps between distinct social groups?

Borgatti and Foster describe four primary aspects of the network paradigm, based on the following two questions: First, Do we care more about improving performance internally, or expanding impact externally? Second, Do we care more about the structural position of individuals, or the flow of communication? These priorities give us four categories:

Social access to resources: Focused on communication flow and internal performance
Structural capital: Focused on network position and internal performance
Environmental shaping: Focused on network position and external impact
Contagion: Focused on communication flow and external impact

In our work, we have encountered four main types of leadership networks:

Peer leadership networks: Focused on building trust among leaders
Organizational leadership networks: Focused on leveraging network position
Field-policy leadership networks: Focused on shaping the environment
Collective leadership networks: Focused on unleashing innovation

Each of the above "four fundamentals of networks" is a list that stands on its own. In the process of writing our chapter for Sage, we synthesized them all into this chart:

What does all that mean? Mostly these two things: (1) more blogging from me soon, with case studies from each of the quadrants above, and (2) pondering why the above four quadrants do not correspond to my beloved "holy trinity of network power," nor to the esteemed standard text SNA: Methods and Applications by Wasserman and Faust.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

New Yorker vs Wired: Is Free the Future?

2009-07-02T14:19:00.004-04:00

This week's New Yorker has a fun piece by Malcolm Gladwell, "Priced to Sell: Is Free the Future?" in which he takes on Chris Anderson's new book: Free: The Future of a Radical Price.

Chris Anderson is the editor of Wired and is famous for coining the phrase "Long Tail." He blogs at http://thelongtail.com and most recently posted, "Dear Malcolm: Why So Threatened?"

I rather enjoy it when the New Yorker takes a smack at Wired. Back in 2006, John Cassidy wrote a NYer article "Going Long: In the new “long tail” marketplace, has the blockbuster met its match?" in which he critiqued The Long Tail (i.e., the book by Chris Anderson).

That article by John Cassidy remains my all-time favorite description of Webonomics (especially in terms of learning a lot by reading a little). I highly recommend Cassidy's and Gladwell's articles as a matched set.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Tweet of submission: @behoppe

2009-06-29T15:45:00.002-04:00

Claire Reinelt has won me over. My first tweet is this quote from Frederick Douglass:

"Find out just what any people will quietly submit to and you have the exact measure of the injustice and wrong which will be imposed on them."

Following the world's greatest RSS feed

2009-06-25T09:18:00.002-04:00

Thank you Paul Toms for sharing your Twitter experiences and other reminisces in response to my last post. I like the Will Leitch article ("Why Twitter is more fun the less you use it") and your quote from it: "Twitter is the world's greatest RSS feed."

Like Paul and Will, I am a fan of RSS. (For those unfamiliar with RSS, it is New Media's version of the AP News Wire; see "RSS in plain English" by Common Craft.)

Much like Will, I find RSS (e.g., Twitter) to be more fun the less I use it. But my idea of "using" is different than Will's. I consider reading to be "using" whereas Will considers reading to be "not using."

A couple examples of how I use and follow RSS feeds without reading:

Over the years I have subscribed to hundreds of blogs and other RSS feeds using NewsGator. Rather than read them, I simply let NewsGator dump them into my Outlook mailbox. Once the content is in my mailbox, my cheap mongo-hard-drive and my free desktop search software (Copernic) keep all that content ready for me. For example, now that I am curious to read about Twitter, I can search my hard drive for "Twitter" and see that Nova Spivak blogged a few months ago that "In the world of Twitter things happen in real-time, not Internet-time. It's even faster than the world of the 1990's and the early 2000's." He goes on to chronicle the acceleration of our lives, concluding: "Twitter is simply faster.... Twitter may overcome the asynchronous nature of the Web. Even search may go 'real-time.'" Having waited 4 months for the moment when I actually care to read Nova's post, I will wait a while longer before I respond to his hope that Twitter will help us "overcome the asynchronous nature of the Web" and make "search go 'real-time'"--two statements that beg for rebuttal.
Another one of my favorite uses of RSS is the right sidebar of the Leadership Networks site, "Recently Noted Links." The links in this sidebar come from an RSS feed that provides Leadership Networks with a non-stop news-ticker of content that is relevant and useful to the audience of the site. Furthermore, this one RSS feed represents the synthesis of hundreds of RSS feeds. You can glimpse under the hood here. It's similar to the previous example, except that the content scrolls down the Leadership Networks sidebar instead of getting archived to my hard drive. I guess the content of that sidebar is my version of what Nova Spivak calls "real-time search." Because I see it that way, the content is presented to embody (not to overcome) the asynchronous nature of the Web: It's available but not interrupting, there when you want it.

Twitter: timing is everything...?

2009-06-23T13:53:00.007-04:00

The majority of my clients and colleagues are using it, but I have not uttered the word until now: TWITTER. I was convinced to break my silence when I saw Time magazine: "How Twitter Will Change the Way We Live."

Here is my version of Time's story: Twitter does to texting what blogging did to email.

So let's get to the root of the matter: Texting. John Cassidy says it better than I can in the October 2008 New Yorker, "Thumbspeak: Is Texting Here to Stay?" Summary of Cassidy: We may be helplessly addicted to crackberries etc, but we are not addicted to typing words with numeric keypads. As soon as we all have QWERTY in our palms, we will then do away with the 140-character barrier and, with that, all the quirks that make txt msgs distinct from emails will quickly die a natural death.

If texting becomes indistinguishable from emailing (grant me that hypothetical just for a moment) how then will Tweeting differ from blogging? I am curious.

[The editor pauses... almost publishes the post... then takes a phone call from a colleague with more Twitter stories. A change of heart occurs.]

No, wait, I have glossed over something fundamental: Timing. Words have rhythm. Even if my version of the Twitter story is technically true (which I think it is), it misses the whole timing thing. That is a big deal, experientially if not technically.

Comments, anyone?

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Beginner's mind and collective intelligence

2009-06-22T09:49:00.009-04:00

It's five years to the day since the first post on Connectedness.

An unspoken theme of those five years deserves recognition today: Beginner's Mind. I heard the phrase last September, when Fred Small preached his very first sermon as the new senior minister at my church.

Without Fred's flair for story-telling, Wikipedia still does a good job of explaining beginner's mind:

"Beginner's mind ... refers to having an attitude of openness, eagerness, and lack of preconceptions when studying a subject, even when studying at an advanced level, just as a beginner in that subject would. The term is especially used in the study of Zen Buddhism and Japanese martial arts.

"The phrase was also used as the title of Zen teacher Shunryu Suzuki's book: Zen Mind, Beginner's Mind, which reflects a saying of his regarding the way to approach Zen practice: In the beginner's mind there are many possibilities, in the expert's mind there are few."

My fascination with beginner's mind often puts me in a bind: In my consulting and my teaching, I am usually invited to take the role of expert, the perspective that will reduce the confusion of many possibilities to the simplicity of the few and the best. Rarely am I invited to help experts take off the focused blinders of their hard-won experience.

Beginner's mind is easily left behind and forgotten. For example, consider that exemplar of communal beginner's knowledge: Wikipedia. The scope and accuracy of this site are deservedly celebrated: Rob Laubacher, Executive Director of the MIT Center for Collective Intelligence, notes that Harvard medical school students prepare for exams using Wikipedia. But where do beginners turn for an introduction to anatomy, once Harvard medical students have claimed Wikipedia as their study guide? I posed that question to Rob. He said it was the first time he had heard the notion that Wikipedia was evolving into a collection of specialized expert-driven beginner-unfriendly articles. We wondered if my experience of Wikipedia being advanced and not at all beginner-friendly was related to the topic my students most want to learn: Web technology.

To a point, perhaps. As a case study of how Wikipedia takes a simple non-Web idea and moves it beyond the grasp of beginners, consider the notion of probability as introduced by Wikipedia and Encyclopedia Britannica. Within its first few paragraphs, before citing a single concrete example of probability (e.g., flipping a coin, rolling dice), Wikipedia asserts thatwhich is easy for them to say. And I mean that truly. Once you have mastered such notation, explaining probability with a language as imprecise as English is really hard. Yet English is the language spoken most often by American students. So where are they to turn? Read Britannica and see for yourself.

When Wikipedia introduces probability as is that what we mean by "collective intelligence," "working wikily," or "wikinomics"? Probably not. But you have to admit it makes sense for Wikipedia to explain probability to us in that way. Why should privileged experts with mastery of a valuable language such as probability theory make it easy for ignorant beginners to join them? The simplest answer is, "Because Encyclopedia Britannica pays them to." In conversations with Rob and others, I have heard of other sensible and even uplifting answers to this question. And so I hope that ignorant and expert alike may be blessed with Beginner's Mind.

PS: See James Surowiecki for a good argument that high-quality information requires high-quality compensation.

PPS: My last sustained post along these lines was this one, in reference to John Ziman's 1968 monograph Public Knowledge--An Essay Concerning the Social Dimension of Science, specifically in the chapter "Community and Communications."

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Organizational network analysis utility: Unleashed

2009-06-05T11:53:00.002-04:00

Back in November 2005 I posted an organizational network analysis utility — a spreadsheet to help process network survey data and load it into network analysis software like UCINET (which is one of my faves, just behind NetDraw and Visone).

Since then, the spreadsheet has been available via email. But I confess that I have more than occasionally fallen behind in emailing copies to those who have requested. Sorry about that.

Now the spreadsheet is available by direct download from the Leadership Networks site here. No more waiting for emails from me.

Not coincidentally, I have been reading posts by Claire Reinelt about unleashing leadership networks — as opposed to sustaining them. Summarizing Ed O'Malley who directs the Kansas Leadership Center, Claire lists 7 practices for unleashing. The 3rd is "let go of the control."

In other words, it's time for me to stop being a bottleneck! Below is more information about the spreadsheet utility, copied from the original Nov 2005 post:

Organizational network analysis provides intuitively compelling pictures of how work really happens, giving us a handle on slippery intangibles that drive the future success of an enterprise.

Although this kind of intuitive analytical power has very wide appeal, its usefulness is limited right now by the unwieldy software tools currently available.

Deep down, making good simple network pictures is inherently complicated, but using network visualization software doesn't have to be. Progress is being made every day. See the newly updated list of SNA software in the right sidebar for some great examples. (And please let me know if I'm missing something.)

Even with the simplest of these tools, my non-technical clients often get hung up right away with the basic task of getting the data in. We power-users can easily forget how hard it was to build our first network, until we see someone else learning for the first time.

Here's an Excel spreadsheet utility my clients and I find helpful. I now make it freely available, in the hopes that more people will enjoy the benefits of seeing the big picture of the network perspective.

The spreadsheet includes three worksheets. One worksheet is the actual survey, which can be modified to suit the specific project. It automatically incorporates the names of the survey population into a drop-down list.
After distributing the survey via email, collected responses can be pasted in any order into a "compiled survey" worksheet:

Then an "automatrix" worksheet converts the compiled results into square matrices that can easily be pasted into available network analysis tools. The matrix calculator makes it easy to manage who opts in or out of the survey, and it provides access to multiple relationships.

If you'd like a copy of the spreadsheet, which includes a copy of a great California Computer case study (permission granted by David Krackhardt), you can download it here.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Searchable leadership networks bibliography

2009-05-27T07:38:00.007-04:00

Our new Link-to-Results site features a categorized searchable bibliography. Of all the pages on the site, this one has generated by far the most feedback. Those whose work we overlooked have been kind to let us know and share with us.

We attempted to synthesize many different fields of work in the bibliography (e.g., leadership development, business, sociology, mathematics). Rather than categorize our references according to their traditional fields, we categorized the references according to why we were interested in them:

Click on each link above and you can see our list of references for that category.

Citing references, categorizing, naming things. These are essential to learning and yet get in the way too. I close with thoughts on naming things, quoting from the Tao Te Ching.

The Tao that can be told is not the eternal Tao.
The name that can be named is not the eternal name.
The nameless is the beginning of heaven and earth.
The named is the mother of ten thousand things.
Ever desireless, one can see the mystery.
Ever desiring, one can see the manifestations.
These two spring from the same source but differ in name; this appears as darkness.
Darkness within darkness.
The gate to all mystery.

--Lao Tsu, Translated by Gia-Fu Feng.

Leadership for a New Era

2009-05-26T16:10:00.005-04:00

"You cannot solve problems with the same level of consciousness that was used to create them."

--Albert Einstein

Leadership for a New Era is an initiative led by the Leadership Learning Community (LLC) with the mission to transform individuals and society by connecting the learning and practice of those who support leadership that is committed to promoting social and economic equity.

Claire Reinelt, Director of Research and Evaluation at LLC, says the initiative is focused on "contributing to a shift in our current leadership thinking from a primary focus on the individual to approaches that support leadership in the context of collective work, networks, communities and social movements...."

Today Claire invites you to share your leadership and learning. She posts on the Leadership Networks discussion forum:

"What do we know about leadership networks that others may not have considered or that they have a tendency to forget? As part of the Leadership for a New Era collaborative learning initiative, we want to share this wisdom with leadership programs and community initiatives, many of which seek to build social capital and network capacity. Here is what I came up with.
Successful networks are not sustained they are unleashed.
Remember that people are nodes in multiple networks.
Bridging across boundaries increases the probability of innovation.
Those on the periphery of a network offer pathways to new allies.
"What is your wisdom?"

I am especially fond of the first bullet! You can respond to Claire here.

PS: For extra credit, I will add this to Claire's question: In reference to the Einstein quote above, what different level of consciousness do we need to solve (as opposed to create) our problems? For example: higher or lower? Someday, perhaps, I will post on why I personally favor the "lower" path.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

New resource on leadership networks

2009-05-22T10:23:00.006-04:00

Claire Reinelt and I have just turned our paper "SNA and the Evaluation of Leadership Networks" (to appear in Leadership Quarterly (Elsevier)) into a full-blown website where practitioners of leadership development can find and share resources: http://link-to-results.com. The site includes the paper, a tagged & searchable database of our bibliography, a discussion forum, case studies, and other resources related to leadership networks.

Below is one of the introductory pages on the site, "Kinds of Leadership Networks":

Leadership networks provide resources and support for leaders, and increase the scope and scale of impact leaders can have individually and collectively. We find it helpful to distinguish four types of leadership networks:

Our choice to focus on these four types of networks grows out of our experience as consultants with clients who fund, run, and catalyze leadership networks. Often our clients are interested in using network mapping or other tools to increase the awareness of leaders about the power of networks, to further catalyze relationships and connections, and to strengthen the capacity of the network to act collectively. There is also growing interest in knowing what difference leadership networks are making.

Our leadership network classification framework is also influenced by the work of Borgatti and Foster (2003), Plastrik and Taylor (2006), among others. We compare these three frameworks with the tables below:

Our Framework
Type of Network	Description of Network
Peer Leadership Network	Leaders who are connected through shared interests and commitments, shared work, or shared experiences. Leaders in the network share information, provide advice and support, learn from one another, and occasionally collaborate together.
Organizational Leadership Network	Leaders who connect to increase performance. Often these are informal connections joining people who are employees of the same organization, such as when an employee seeks advice from a colleague other than her supervisor.
Field-Policy Leadership Network	Leaders who have a shared commitment to influencing the world around them (e.g., the framing of a particular issue, underlying assumptions, and standards for how things get done). These networks make it easier for leaders to find common ground, mobilize support, and influence policy and the allocation of resources.
Collective Leadership Network	People who self-organize around a common cause. Network members exercise leadership locally and sometimes connect on a large scale. These networks may be driven by a desire to achieve a specific goal, or simply by the desire of each member to belong to something larger than oneself.

Borgatti and Foster approach networks with a more conceptual emphasis than ours. They present a very broad network paradigm within a two-by-two matrix. We highlight below how the four quadrants of their matrix correspond most closely to our framework of four types of leadership networks:

Borgatti and Foster (2003)
		Goal used to explain network
		Actor performance evaluation	Properties of resource diffusion
Mechanism used to explain network	Structural position of actors in network	Structural Capital (Organizational)	Environmental Shaping (Field-Policy)
	Flow of resources through ties	Social access to resources (Peer)	Contagion (Collective)

Plastrik and Taylor's Net Gains handbook speaks directly to practitioners (network builders) seeking social change. Their framework also maps neatly onto ours:

Plastrik and Taylor (2006)
	Connectivity Network (Peer)	Alignment Network (Organizational)	Production Network (Field-Policy)
Definition	Connects people to allow easy flow of and access to information and transactions	Aligns people to develop and spread an identity and collective value proposition	Fosters joint action for specialized outcomes by aligned people
Desired Network Effects	Rapid growth and diffusion, small-world reach, resilience	Adaptive capacity, small-world reach, rapid growth and diffusion	Rapid growth and diffusion, small-world reach, resilience, adaptive capacity
Key Task of Network Builder	Weaving-help people meet each other, increase ease of sharing and searching for information	Facilitating-helping people to explore potential shared identity and value propositions	Coordinating- helping people plan and implement collaborative actions

The fundamental goal of our framework is to help practitioners of leadership development - to explain when and how to use social network analysis as an evaluation and capacity-building tool.

All people who are dedicated to developing and supporting the emergence of leadership must understand how to create, develop, and transform leadership networks. We hope our work will inspire more evaluation research on leadership networks and on how to harness and use the power of social network analysis for the collective good.

Student leadership: thank you Sidney Efromovich

2009-05-14T17:00:00.006-04:00

Collaborating with Nat Welch of CFAR has taught me the virtues of Found Pilots and the Campaign Approach to Change -- the progress you seek already exists as deviant behavior within the present moment.

I was "lucky" (I keep telling myself) to find lots of deviant behavior among my most recent cohort of students at Boston University. For example, the most popular student project featured a wonderfully deviant title: "Ben Timmins worked a ton, and all he got was this website."

My favorite found pilot was the unauthorized work of one Sidney Efromovich, BU '09, founder of the Hug Don't Hate Movement. Starting from day one, Sidney typed all my lectures into an encyclopedic set of Web pages. The whole semester -- every example I explained, every diagram I drew, every definition, equation, formula -- all of it Sidney not only included in his site but also improved in the process.

Having worked 3 years (a lifetime?) to develop a beginner-friendly and conceptually rigorous curriculum for the undocumented field of Web Science, I am very grateful to Sidney for so artfully, faithfully recording our spring 2009 improvisation on that theme. I am even more grateful to Sidney for giving me every artifact of his Web site as a parting gift. An honor and a privilege to have worked with you, Sidney!

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

SNA and Leadership Networks

2009-03-23T11:22:00.003-04:00

Claire Reinelt and I are pleased to share our paper, "Social Network Analysis and the Evaluation of Leadership Networks, " which is due for publication in a special issue of Leadership Quarterly (Elsevier) on the topic of evaluating leadership. Look for it on news stands in early 2010.

Social Network Analysis and the Evaluation of Leadership Networks (PDF)

Bruce Hoppe, PhD
Connective Associates LLC

Claire Reinelt, PhD
Leadership Learning Community

Abstract
Leadership development practitioners have become increasingly interested in networks as a way to strengthen relationships among leaders in fields, communities, and organizations. This paper offers a framework for conceptualizing different types of leadership networks and uses case examples to identify outcomes typically associated with each type of network. One challenge for the field of leadership development has been how to evaluate leadership networks. Social Network Analysis (SNA) is a promising evaluation approach that uses mathematics and visualization to represent the structure of relationships between people, organizations, goals, interests, and other entities within a larger system. Core social network concepts are introduced and explained to illuminate the value of SNA as an evaluation and capacity-building tool.

Table of Contents

Introduction	1
Classifying Leadership Networks	3
Introducing Social Network Analysis	4
Evaluating Leadership Networks	8
Peer Leadership Networks	10
Organizational Leadership Networks	14
Field-Policy Leadership Networks	19
Collective Leadership Networks	24
Issues and Risks of SNA	28
Future research	33
Conclusion	36
Bibliography	37

Full Paper here.

It has been great to work with Claire on this paper, and we are grateful to the folks at Leadership Quarterly for providing us with helpful editorial suggestions and generous permission to post this version of the paper.

Stay tuned for posts about specific excerpts & themes of the paper...

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Evil-Doers at Sunbelt in San Diego

2009-03-10T12:43:00.005-04:00

Tomorrow I fly to San Diego to attend Sunbelt, the annual SNA extravaganza.

The keynote address, by Phillip Bonacich, is "Using Social Networks for Evil":

"Many uses of the network approach in sociology involve pro-social behavior.... Yet, individuals use the networks they are involved in for their own selfish and malign purposes....

"As those who have studied social dilemmas have demonstrated, anti-social behavior can be fun and profitable.

"What I wish to explore in this talk is one form of anti-social behavior, one that I have been thinking about recently - the exploitation of the weak and dependent in networks of social exchange and violations of the norm of reciprocity."

I am looking forward to hearing more about that! And perhaps I will meet some of you (readers) in San Diego this week.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Role ecologies in online networks: Gleave, Welser, Lento, Smith

2009-02-20T10:19:00.005-05:00

Marc Smith, who until recently was chief sociologist in residence at Microsoft, writes a notable blog at http://www.connectedaction.net. A couple weeks ago Marc posted this award-winning paper, co-authored by Eric Gleave, Howard "Ted" Welser, and Tom Lento: “A conceptual and operational definition of 'Social Role' in Online Community”. It's a great piece of work.

One of the stated goals of the paper is to encourage future research into "the analysis of communities as role ecologies."

As my contribution to that goal, I'd like to point out another notable paper: “Network Role Analysis in the Study of Food Webs: An Application of Regular Role Coloration” published by Johnson, Borgatti, Luczkovich and Everett in 2003.

Johnson et al also state their goal clearly: "With this paper we hope to begin a dialogue between the fields [of ecosystem ecology and social network analysis], by applying advanced social role theory and methods to the study of food webs. "

I am a bit puzzled that those who would encourage future research into the analysis of communities as role ecologies do not cite the work that actual ecologists are doing in network role analysis. Perhaps if I knew more sociology or more ecology I would appreciate the reasons for this.

However it works out, it would be fitting if two different camps researching "role ecologies" were to find themselves at a loss to cross-fertilize. For as we celebrate the extended 200th birthday of Charles Darwin, author of "On the Origin of Species," let us note that one of the most practical definitions of a species is this: a population of organisms that can create offspring with their cohorts but not with anyone else. In other words, once a species comes to exist, never again will it cross-fertilize with other species. The result is Darwin's famous "Tree of Life," the one and only figure in his most famous book:
As I learned while reading Darwin's 200th essays in the NY Times last week, the one-way branching of this tree -- the permanent disabling of cross-fertilizing -- seems to be closely related to the same genetic mechanisms that protect a species from disease. (Intrepid cross-fertilizers should compare this to Ron Burt's notes on network closure.)

A "tree" is also a very specific kind of network, described very nicely in a recent paper by Skye Bender-deMoll on SNA & human rights. For those still celebrating Darwin's birthday, Bender-deMoll's definition is deliciously ironic: "Trees are hierarchies.... Pure trees are not found very often in naturally-occurring networks, but they are frequently used in classification systems or any situation where a strict hierarchy is imposed." Purposeful classification & hierarchy... just the things that Darwin so controversially discarded from the ecological world-view when he theorized the purposelessness of natural selection.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Six ways to make Web 2.0 work: Hoppe vs McKinsey

2009-02-19T11:39:00.005-05:00

Nat Welch brought to my attention "Six ways to make Web 2.0 work" in the McKinsey Quarterly of Feb 2009.

Here are the six ways (quoted verbatim):

The transformation to a bottom-up culture needs help from the top
The best uses come from users -- but they need help to scale
What's in the workflow is what gets used
Appeal to the particpants' egos and needs -- not just their wallets
The right solution comes from the right participants
Balance the top-down and self-management of risk

Maybe it's because I am jealous of the clout wielded by McKinsey, but I do find the above list awfully repetitive. Someone please help me understand the important distinctions between numbers 1, 2, 5, and 6. I'll give the benefit of the doubt to 3 & 4 for being not repeats of 1, 2, 5, 6.

In preparation for an upcoming Web 2.0 panel discussion hosted by the Boston Club, I made my own list--with inspiration & edits from Nat W.

Bruce's Technology Tips

Focus on your business goals and let those drive your technology strategy. For example, consider the following goals:

Sales
Marketing
Recruiting
Talent management
Business development
Innovation of core products & services

Each one of those goals implies a different technology strategy, so it's important to know which goals matter as a basis for evaluating which technologies are helpful.

Web 2.0 Strategy Map

Technology for business is largely about storing, finding, synthesizing, and communicating information. Think about how these different tasks relate to your specific business goals. The table below summarizes how some Web 2.0 technologies relate to finding and synthesizing information:

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Ethics, Social Networks, and Web 2.0

2009-02-11T08:39:00.006-05:00

Earlier this week the Human Resource Planning Society hosted a convention on Social Networks and Web 2.0. Nat Welch (CFAR) and I co-led a session on "Organizational Barriers and Web 2.0: Don't just sit there; find something." Afterward we were part of a panel discussion on ethics, social networks, and Web 2.0.

Somewhere there is a joke to be written about the time when a lawyer, a computational sociologist, and a human resource director all answer questions from St. Peter about ethics. Playing the straight man in the joke, my conversation with St. Peter will be a discussion about informed consent. Do people in my life know what they are getting into, and can they exercise choice based on that knowledge?

In many ways, the "informed" part is far slipperier than the "consensual" part of this combination (e.g., dating). And so it is with social network surveys. Years ago I read Borgatti and Molina's framework for ethics and SNA, and their paper has been a trusted compass of mine ever since. Mostly, it reminds me to respect the privacy of my clients and their employees (i.e., to offer them informed consent). Based my experiences since then, I have made the following chart that summarizes how privacy and informed consent are so problematic in a network context:

Lack of Privacy in Network Surveys
	Traditional survey	Network survey
Questions: 1^st-person vs. 3^rd-person	Each individual reports information about himself.	Each individual reports information about others by name.
Results: averages vs. specifics	Responses are aggregated so that individual respondents and non-respondents cannot be distinguished.	The presentation of results reveals specific responses attributed to specific individuals.
Visibility: informed consent vs. leap of faith	Survey results allow each individual to compare himself silently with the group average. Each individual can then decide what to share about himself with whom.	Survey results expose how each individual is seen by others. Each individual has no ability to preview what others have said about him before it is published.

For me the insight of the above chart is the separation of all three rows. Each of the them can be considered as an independent risk factor with its own unique set of mitigation strategies.

All the LinkedIns and Facebooks of the world are tackling these three issues head-on (and surely more that I have not thought of).

As for social network surveys, I am not aware of one that allows truly informed consent: the ability to preview what others say about you before consenting to publication of that information. Perhaps my readers can enlighten me.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Lincoln and Darwin on Networks and Web 2.0

2009-02-05T09:35:00.005-05:00

"Online social tools are great weapons for world peace and unity."

--Overheard at a discussion about LinkedIn, Blogs, and Twitter.

How appropriate that peace and unity cross my desk as we approach the 200th birthdays of Abraham Lincoln and Charles Darwin. Their historically coincidental births (12 Feb '09) and monumental legacies were brought to my attention by the latest cover of Smithsonian magazine, an issue I highly recommend.

Each of these great men speaks to the ages in a way that changes from era to era and from person to person. For me now, Lincoln shrewdly speaks of our sacred devotion to Liberty and equality as he leads the bloodiest war in American history:

"Four score and seven years ago our fathers brought forth on this continent, a new nation, conceived in Liberty, and dedicated to the proposition that all men are created equal. Now we are engaged in a great civil war, testing whether that nation, or any nation so conceived and so dedicated, can long endure." (Read on.)

Meanwhile, in one of the greatest discoveries of science, Darwin writes about the consequences of the simple truth that no one is created equal:

"As many more individuals of each species are born than can possibly survive; and as, consequently, there is a frequently recurrent struggle for existence, it follows that any being, if it vary however slightly in any manner profitable to itself, under the complex and sometimes varying conditions of life, will have a better chance of surviving, and thus be naturally selected. From the strong principle of inheritance, any selected variety will tend to propagate its new and modified form." (Read on.)

Darwin writes reluctantly, forced by outside events into a public announcement of his work, which he kept secret for many years in part to avoid the backlash he knew it would generate.

That backlash remains strong (at least in America), resulting in notions like intelligent design. Personally, I find intelligent design to be an absurd bastardization that dishonors both science and religion. And yet paradoxically I am continually tempted to take on the role of intelligent designer--pronouncing truths from the digital scriptures. I guess that's easier than emulating Lincoln or Darwin.

In praise of editing

2009-01-21T09:37:00.004-05:00

Thank you to everyone who commented on the Working Wikily thread. Comments on this blog are rare (which is probably to be expected) and 99% of them are complaints about kitchen appliances (which is agonizingly hilarious), and so it is a wonderful surprise to receive comments about a topic of ongoing interest to me.

A blizzard of holiday celebrations have passed since then, so to recap: In my Working Wikily series of posts, I spoke to the healthy priorities of those who do not write and publish on wikis and merely use information shared by others. This seemed to provoke violent agreement.

During the holiday season, I thought a great deal about those who do write and publish. The contemplation was entirely self-serving: Claire Reinelt and I spent those months slavishly editing our paper, "SNA and Evaluation of Leadership Networks."

We are optimistic that the result will be accepted for publication in Leadership Quarterly (LQ), and hopeful that LQ will allow us to share the manuscript before its estimated publishing date in 2010. You'll see it here first, if/when LQ does allow us to share it.

Most germane to this post, Claire and I are incredibly grateful to the anonymous reviewers of LQ. Their extremely pointed criticisms and their constructive suggestions for improvements enabled Claire and me to improve our originally submitted draft into something exponentially better. The extra time also gave Claire a chance to convince me to read Skye Bender-deMoll's overview of SNA. Again, I am grateful.

In my networked world, I very rarely encounter editorial demands as stringent as those imposed by an old-school academic peer-reviewed printed-on-paper journal. What an invaluable experience this has been.

More often in a networked world, editorial demands are sub-consciously self-imposed. Every day, it gets easier to avoid those with a different point of view and simply google our way to information that confirms what we already believed. That, at least, is what is suggested by this recent press release from the NSF, which I originally commented about here. Of course, the NSF only suggests that this phenomenon applies to the behavior scientists. Perhaps we non-scientists are more dedicated to the tireless pursuit of truth.

Certainly I credit Skye Bender-deMoll for scientific pursuit of truth. In this May 2008 paper, Skye presents the network Tree of Knowledge; then presents the Babel-izing confounding of terminology and lack of synthesis that characterize the field; and then suggests some editorial advice that is worth taking. For example:

"Although many people are advocating that network techniques will help a great deal with evaluation tasks, there have not been any large scale systematic studies comparing the various pilot projects. Most projects have been fairly small, both in sizes of networks and numbers of participants.

"The majority of projects appear to be doing more diagnosis than assessment. This may be partially because in most cases there is no “known standard” for comparing assessments. Also, researchers tend to be cautious because the data collection is not rigorous or comprehensive enough to be safely used for evaluation at this time.

"Although a few of the academic studies show high methodological maturity, much of the work still seems quite exploratory. In several papers the insight appears to come more from the in-depth interviews and data collection process, with the network analysis component serving as a parallel approach."

Wikis, surveys, and webwhompers

2008-12-11T16:58:00.002-05:00

Continuing on the thread of when have I seen wikis work the best... In my last post I answered that I have seen wikis work quite well when they are tightly controlled. I described the LeaderNetwork wiki, which only allows editing by Claire Reinelt and me.

Another good way of controlling a wiki is not by limiting the number of editors (as in the previous example) but by limiting the contributions asked of each editor.

Used in this way, a wiki is quite similar to an online survey. The wiki begins with a clear list of questions and a well-defined framework to hold each response contributed by each wiki editor --- just like SurveyMonkey. However, a wiki-survey has two important differences:

Transparent sharing of all wiki-survey responses is a given. There is no waiting for the survey administrator to publish anything, no option for the survey administrator to hold anything back.
The questions themselves can be added to and/or edited on the fly by wiki-survey respondents. This frees the survey administrator from having to ask just the right questions; if someone does not see the question they wanted to answer, they can add that question in a place where everyone can respond to it.

One of my favorite wiki-surveys is this one, which I have used to run a contest that recognizes the most popular student project of the semester. It is a simple and effective wiki-survey that leverages option #1 heavily and ignores option #2. I have previously posted two case studies about its use on these pages: "Pros and cons of male enhancement" and "Delete all your links, except to me." I have modified it for use in many client engagements as well, fully leveraging both options #1 and #2.

This fall I significantly upgraded my pseudo-survey technology by abandoning the wiki platform altogether. You can see my post-wiki pseudo-survey at http://webwhompers.net, where the blood from my students' recently fought competition is still fresh.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Wiki Whomping

2008-12-04T16:54:00.004-05:00

"When have I seen wikis work the best?" Thanks to Noah Flower for posting his thoughtful response to my last post (about working wikily), and closing with that question.

By way of answering, I'd like to quote from the pre-eminent prophet of working wikily, Clay Shirky. In his award-winning essay "A group is its own worst enemy," Shirky states, "Prior to the Internet, the last technology that had any real effect on the way people sat down and talked together was the table."

You can click here to read my original argument that Shirky is crazy if he really believes that. Today, instead of arguing against Shirky, I'd like to use his quote to put Noah's question in clearer context:

"When have you seen tables work the best?"

If you find that question confusing, good. Tables are such a fantastic technology for collaboration, and so flexible in the ways we can use them, that asking for "best example of using a table" is more of a Rorschach test than a question. More specifically, it's a great question for a furniture salesman to ask, as the person answering will suddenly feel an urge to find some connection between tables and whatever "works the best."

Answering Noah more earnestly (sort of), I have seen wikis work very well when they are tightly controlled. For example, Claire Reinelt and I use a wiki to publish our favorite reading list about SNA and leadership networks for social change. Our reading list is a joint effort that neither of us could have assembled alone. The most important feature of the site, however, is that no one can edit the wiki but me and Claire.

I'll close today's post with this passage from Wikipedia. It's from an article on participation inequality, but it also works well as a manifesto for Wikipedia's own governance, which is much more tightly controlled than it used to be:

"A major reason why user-contributed content rarely turns into a true community is that ... a few users contribute the overwhelming majority of the content, while most users either post very rarely or not at all. Unfortunately, those people who have nothing better to do than post on the Internet all day long are rarely the ones who have the most insights. In other words, it is inherent in the nature of the Internet that any unedited stream of user-contributed content will be dominated by uninteresting material."

Next time we'll answer the question, "When have I seen social bookmarking work the best?"

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Working Wikily

2008-12-02T15:42:00.003-05:00

Last month the Monitor Institute launched a blog http://workingwikily.net about how the social sector is adopting the new tools, strategies, and practices of networking.

They explain here that "Working Wikily" was coined "to describe the new ways that people are applying network theory and networked technology to do the work they’ve always done in a more collaborative form and also to begin working in new ways altogether."

As my contribution to "Working Wikily," I'd like to offer a reality check on what happens when people use a wiki. Before I continue, however, let me make clear that (1) collaboration is great, (2) wikis are great, and (3) the reality check I am about to deliver is aimed at people who associate "collaboration" with "wiki" and thereby set themselves up for disappointment when they learn this the hard way:

Jakob Nielsen summarizes Web collaboration in general with the 90-9-1 rule as pictured below.
90% do nothing, 9% do a little, and 1% do practically everything.

Blogs are even more skewed than average Web sites, with 95% doing nothing, 4.9% doing a little, and 0.1% doing practically everything.

Wikis are the most skewed of all.

Most community facilitators I know who have set up wikis lament that they can't get anyone else to edit it without resorting to bribery. That is 100% doing nothing while one outsider does everything.

With a hugely successful wiki like Wikipedia, the ratio is slightly better, 99.8% percent do nothing, 0.197% do very little, and 0.003% do practically everything.

The above dose of reality is called "participation inequality" by Nielsen. Let me reiterate that I do not see this inequality as a problem, even though Nielsen presents it that way (as would, I suspect, many who set out to "work wikily" and end up proving Nielsen's point).

Thank you to Laurie Damianos for alerting me to these statistics during her presentation on MITRE's use of social bookmarking on their corporate intranet. Her experience at MITRE was consistent with the general trends claimed by Nielsen. Unlike many others in her position, though, she did not get discouraged by low participation, nor did she try to change it. Instead, she did a great job explaining to the powers-that-be that MITRE's social bookmarking system was working great, even with most people contributing nothing.

So let's raise a toast to the 99.8% who have perfected the most popular way of "working wikily" -- those who do nothing and, when they feel like it, coast off the hard work of the 0.003% who give it all away.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Geographic networks

2008-11-21T11:05:00.007-05:00

Geography (or spatial arrangement) of nodes is often an important factor in network dynamics. Though it is straightforward to map geographical information by itself, mapping that information simultaneously with network data is quite a challenge.

In collaboration with Holly Massett and her team at the National Cancer Institute, I have been tackling the geographic + network mapping problem head on. Holly and I recently presented some of our results, and she graciously gave me permission to share them.

What happens when we draw a network map with geographically located nodes? We get a map with lines on it:
The geography is plainly apparent, but the network structure is all but invisible. That's a shame, because the network structure hidden above is actually quite striking when you redraw the above network using traditional network layout techniques:
Now we can clearly see that there is one node that bridges between two distinct clusters.

As a simple first step toward integrating these two important views of the above collaboration network, I created this slide show, which morphs back and forth between pure geography and pure network information, showing the interaction of the two along the way (RSS readers must view my actual blog to see this):

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Working the math in your favor

2008-11-19T09:16:00.003-05:00

Last week I was part of a panel discussion about technology and business. Forty or fifty accomplished businesswomen attended--I was the only man in the room. In hindsight, this was a perfect opportunity for me to focus on Bion's three pillars of group behavior (or at least the first of those three pillars, having the mating partner ratio so heavily in my favor); however, I confess I occasionally let my thoughts drift from that #1 priority and instead contemplated the diverse perspectives on technology represented in in the room.

The audience was predominantly business-savvy and ranged from the tech-curious to the tech-confused. It was not the most receptive setting for preaching a Taoist bliss of ignorance, but that's what I pitched, with lines like "the best technology is whatever you're using now"; "reading email when you receive it lowers your IQ more than chronic pot-smoking"; and "technology is implemented to benefit its creators, not its users, so look for technology where the users and the creators are the same."

The room was filled with questions about LinkedIn and Twitter. I realized that LinkedIn has taken hold of a much wider business audience than it had when I last disparaged it on these pages 2-3 years ago. Sensible successful business people speak with complete earnestness about the 500,000 people in their LinkedIn network, and I am speechless.

I have some hope. My LinkedIn network has 2,850,200 people, including 16,927 new connections in just the last 4 days. Before I leverage all of them, however, I sense that LinkedIn is giving me an opportunity to update this old joke:

A museum guide leads a group of tourists through a dinosaur exhibit. Stopping at an impressively scary skeleton baring its fossilized teeth, he says, "This T-Rex is 70 million and 3 years old." One of the tourists responds, "Wow! How do they figure that out so precisely?" The guide responds, "Well, when I started working here, this skeleton was 70 million years old, and that was 3 years ago."

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Viewing network data in Excel... with banana

2008-10-20T09:41:00.006-04:00

Today I received an invitation from Harvard's Program on Networked Governance to watch Marc Smith demonstrate the powers of .NetMap --- a network visualization tool that runs inside Excel 2007. Maybe I will upgrade my MS Office and check it out; the screen shots look good.

On a more personal note, my BU faculty site is up. The site demonstrates what any monkey can do after enough time hanging with my students.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Structural equivalence: related tags in social bookmarking

2008-09-24T09:03:00.000-04:00

In my "Holy Trinity of Network Power," structural equivalence is conceptually the most obscure. But practically speaking, it is easy to use. For example, searching for "sna" with the social bookmarking engine delicious provides the following:

I have enlarged and highlighted the "Related Tags" provided by delicious. This sort of information helps people find and learn from others with shared interests, using structural equivalence, regardless of how many degrees of separation they have on Facebook or LinkedIn. I'll expand more on this idea soon.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Structural equivalence: social bookmarking on a corporate intranet

2008-09-22T10:48:00.000-04:00

Last week Laurie Damianos of MITRE presented to the Boston KM Forum, sharing her experience implementing a social bookmarking system within the enterprise.

For newbies, I often describe social bookmarking as similar to Amazon.com in its ability to track both people who read the same "books" and "books" that share common audiences--whether those "books" are literal or metaphorical. For the mathematically curious, structural equivalence is the underlying principle. Also, here's an introduction to social bookmarking I wrote a while back. Bill Ives has written a few times about applying social bookmarking within the enterprise, including specific references to MITRE's and IBM's experiences.

Laurie's presentation was great and left me feeling more excited than ever about business applications of social bookmarking. But I also left feeling puzzled by the response I got to one of my (many) questions. One way MITRE manages its in-house social bookmark system is by deleting bookmarks created by people who have since left the company. When I asked if there had been any debate within MITRE about deleting this information, I got two responses from the group: (1) Bookmarks are deleted, but the content (referenced by the former bookmarks) remains; and (2) Without the context of an owner, what good is a bookmark?

These two assertions strike me as odd, especially coming from a group that aims to solve the "lost knowledge" problem (e.g., Dave DeLong).

Deleting bookmarks of ex-employees seems to me on a par with burning bibliographies of articles whose authors are dead. After all, the artices and their references still exist. Furthermore, the authors are no longer around to provide context to their bibliographies. So why don't we save library shelf space and rip out all those bibliographies? Anyone who has ever done research can answer that question.

If bibliography-burning seems extreme, here's a milder example much closer to the MITRE reality: Amazon.com could save tons of disk space if it deleted the purchase records of people who haven't bought anything for the past year (i.e., those who have "left Amazon"). I wonder what the managers of Amazon would say to someone who suggested this strategy and argued that (1) the products purchased are still listed, and (2) the purchasers have left, so why bother to keep those records?

As pioneers of collaborative filering, managers at Amazon would probably recognize purchase records of the departed as a valuable resource. Acquiring those records in the first place is one of the biggest competitive advantages a service like Amazon can achieve--commonly known as surmounting the "cold start problem."

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Rob Cross Braintrust Keynote and Density

2008-09-19T07:53:00.001-04:00

As an example of network-cluster-driven-behavior, last time I suggested a simple way to stereotype the work of Rob Cross. The first row of the table below, from his "Braintrust Keynote" presentation, was my Exhibit A:
The other rows of the above table deserve comment as well. Let's focus today on the third row, Centrality, with apologies to those who thought that my recent series on network centrality was finished.

In all my posts on centrality, I never actually described a mathematical formula for calculating it. There are quite a few reasonable ways to define centrality. See this post for links to a few of them. We see above that Cross's Braintrust Keynote describes centrality as the "average # of relationships per person." Unfortunately, this notion of centrality has nothing at all to do with what other people mean when they say "centrality."

First, a preliminary clarification: "Centrality" is most commonly used to describe a single node in a network, but it is also used to describe a global property of an entire network (much like "centralization" in the bottom row of the Braintrust Keynote table above). So we should be clear that "average # of relationships per person" is a global property of an entire network.

With that in mind, observe the following two networks that have exactly the same number of nodes, exactly the same number of edges, and hence exactly the same value of "centrality" or "average # of relationships per person":
I don't think too many people would describe the above two networks as having equal centrality, despite the Braintrust Keynote assertion.

It's a shame to equate "centrality" and "average # of relationships per person." They are two of my most favorite network metrics. I have devoted enough recent bandwidth to centrality to make clear my affinity for that metric. Soon, I will explain why I like "average # of relationships per person" as an alternative to density (top row of the Braintrust Keynote table) that is much less susceptible to the network size bias noted by Kathleen Carley.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Clustering: Guide to Stereotyping Rob Cross and Kathleen Carley

2008-09-11T10:23:00.001-04:00

Recently I mentioned how network clustering on the WWW indicates that Rob Cross and Kathleen Carley each have their own close-knit camps that co-dominate the world of "organizational network analysis." Before that, I shared Ron Burt's point that such close-knit camps are known not only for amazing productivity but also for stereotyping outsiders.

I am outside both the Cross and Carley camps, but I enjoy stereotyping as much as anyone, so today I provide convenient superficial labels with which my readers can simplify the contributions of these two notable network leaders.

Guide to stereotyping Rob Cross and Kathleen Carley:

Rob Cross provides stories for business
Kathleen Carley provides computer models for the military

Wasn't that easy? Now let's look at one example of each stereotype.

(1) The recent research of the Network Roundtable features Cross's "Braintrust Keynote Presentation." Here is his third slide:
Note the simple and compelling story in the top row of the table: Network density within and across departments of less than 20% indicates little collaboration. If you read the actual presentation, you'll see that the "target density" is only 9.4% because the current density is less than half that, so the target is a healthy step up towards 20%. I will skip the other rows of the table for now.

(2) Kathleen Carley's camp responds to the above story with the following article:
As far as stories go, this article sucks. But look, it is classified under "statistical simulation," because the researchers use computer programs not only to analyze networks, but also to create the very networks that they study (no pesky data collection necessary).

For those whose eyes are glazing over, let me summarize the computer model punchline with a picture. The following three networks all have exactly the same density, 20%; and so according to Cross each of the three networks below has exactly the minimum recommended allowance of connectivity to indicate collaboration:
As you can see, density of 20% means different things depending on how many nodes are in the network.

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Read email or smoke pot---The choice is yours

2008-09-09T14:29:00.000-04:00

While playing hooky from Rob Cross's school of networks, I am free to indulge in all kinds of reckless neuron-destroying behavior. One option is attending to email, which is even better than pot-smoking at reducing IQ.

Chances are you know someone with an email problem. Give them the gift of 5 additional IQ points by inviting them to take this survey, created by Peggy Kuo at the University of New South Wales, Australia:

Email Addiction in the Workplace.

Link to survey: http://www.questionpro.com/akira/TakeSurvey?id=1023102

The aim of this study is to determine if Email Addiction exists in the workplace; if so what factors contribute to it and how can it be measured or determined. In addition we also aim to determine the impacts it has on productivity in the workplace.

If you decide to participate, you will be asked to complete an online survey. It is envisaged that the survey will take between 5-10 minutes to complete. There are no known or foreseeable risks associated with the survey.

Network Clustering: Rob Cross and Kathleen Carley

2008-09-05T08:26:00.000-04:00

Next Monday, Sept 8, begins the 2-day Network Roundtable Fall Conference. Rob Cross at UVA has led the Network Roundtable from its inception. He and his colleagues have quite an agenda planned for their time in DC.

My regular readers with sharp eyes may have noticed Rob Cross in a recent post of mine. That post introduced network clustering with an example --- a WWW clustering analysis of "organizational network analysis" computed by Grokker:

One of my favorite metaphors for clustering analysis is the table of contents. It is useful for seeing the big picture, all-inclusively, broken down into sub-categories. In an organizational network setting, a natural application would be identifying communities of practice (including those that don't yet recognize themselves as such).

Continuing with the book metaphor, we can see that the WWW authors of organizational network analysis have devoted "chapters" to these topics:

Social networks
Organizational systems
Public health
Information management
Knowledge
Tools
Rob Cross
Kathleen M Carley
Other

Most of these "chapters" are based on fields or methods of work. Two "chapters" stand out for being based on individual people.

Another way to view these "book chapters" is as "closed networks" (relatively speaking), as I described in my last post. I refer my readers again to that post, this time keeping Rob Cross and Kathleen Carley in mind. It's fun to speculate how the Cross and Carley camps employ stereotypes to describe their counterparts.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Network Clustering: The Power of Reputation

2008-08-20T08:32:00.003-04:00

As we leave our series on network centrality and begin an exploration of network clustering, who better to help us bridge the gap than Ron Burt. Burt is perhaps best known for his amazing network-based research on innovation and the source of good ideas, which brought "structural holes" to the world's attention. In Brokerage & Closure he expands these ideas into book form and brings additional attention to "closure," a key trait related to network clustering.

Very briefly, closure refers to the interconnectedness of one's contacts: When my contacts don't know each other, my network is "open," and when they do know each other, my network is "closed." Assuming that I am #1 (naturally), two extremes of open (left) and closed (right) are pictured below:"Open" and "closed" are pretty much the same as bridging and bonding, as I have discussed before:

For more discussion of network closure, I recommend Burt's online notes for his executive MBA course, "Strategic Leadership," specifically the chapter on Closure, which I would sum up with these two points:

The peer pressure created by closed networks builds commitment and productivity
The peer pressure created by closed networks reinforces groupthink and promotes mindless stereotypes

Click on the image below and you can read what Burt himself says:

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NSF and Google-induced stupidity

2008-08-13T14:43:00.000-04:00

The NSF has just published Fostering Learning in the Networked World: The Cyberlearning Opportunity and Challenge. Reading it reminds me of why I bailed out of academia. The introduction starts: "To address the global problems of war and peace, economics, poverty, health, and the environment, we need a world citizenry with ready access to knowledge about science, technology, engineering, and mathematics."

Wow. Another thing the world citizenry needs is a ban on vapid topic sentences whose only purpose is to inflate the perceived importance of the author's pet project.

In the NSF-funded land of cyberlearning, there is a five-tiered hierarchy of human interaction, represented by the cool picture below: The report explains the picture thus: "[The figure above] depicts historical advances in the communication and information resources available for human interaction. Basic face-to-face interaction at the bottom level requires no resources to mediate communication. The second wave of resources offered symbol systems such as written language, graphics, and mathematics but introduced a mediating layer between people. The communication revolution of radio, telephony, television, and satellites was the third wave. The outcomes of the fourth wave—networked personal computers, web publishing, and global search—set the stage for the fifth wave of cyberinfrastructure and participatory technologies that are reviewed in our report."

So, we are going to solve the "global problems of war and peace" with a framework that explicitly omits mediation from the realm of face-to-face communication. I wonder how much cyberinfrastructure South Ossetia would need to put this framework to use.

Next time I will get back on my network clustering thread again...

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Clustering: The Un-Google

2008-08-07T12:30:00.002-04:00

Having finished our series on network centrality, we now approach its most natural complement: network clustering.

An easy way to appreciate the usefulness of network clustering is to try search engines that (unlike Google) are not centrality-driven. There are quite a few such search engines out there. They are great at providing a sense of direction within a previously unknown field --- when you're not yet sure exactly what question you're asking. In contrast, Google is better when your query is more specific, or when you just don't care about the rest of the forest, dammit, and want to find the biggest most popular tree ASAP.

Below are two examples of how non-centrality-based search engines display the WWW of "organizational network analysis". Click on either image to go to the search engine pictured.

There are dozens more search engines listed here by search engine junkie Bill Sebald.

I hope you enjoy the Un-Google world. Soon I'll say more about understanding this world with the help of network clustering.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

NetDraw / UCINET tutorial; networks = organizing

2008-08-05T14:11:00.003-04:00

Link of the week: Network Mapping as a Diagnostic Tool, by Louise Clark. This is the best NetDraw user's guide I have seen. Thanks to Cai Kjaer at www.onasurveys.com (via his helpful wiki) for alerting me to this resource.

A few weeks ago I got an anonymous email with nothing but this quote:

"Science is organized knowledge. Wisdom is organized life."
--Immanuel Kant

That is some interesting spam. It got me thinking: Is "organized" really the fundamental property of science and wisdom? No, I decided; it's just a word making a pithy quote. I then forgot the matter, only to remember it today, when I read "Using Emergence to Take Social Innovation to Scale," by Meg Wheatley and Debbie Frieze of The Berkana Institute. They say:

"Networks are the only form of organization on this planet used by living systems."

True enough, but I claim their statement is too weak. I would rephrase it "Networks = Organization." If you disagree, please send me a counterexample in the form of an organizing principle that does not invoke things (i.e., nodes) and relationships (i.e., links). And feel free to consider other planets, non-living systems, dark matter, alternate universes, etc. You must also agree to let me use confusing mathematical machinery in order to refute your counterexample. The best "counterexamples" I have so far are organizing by space and time. For example, jellyfish organize by drifting near the surface of the ocean, and people organize by sleeping when it's dark.

Once you accept that Networks = Organization, Wheatley and Frieze's assertion becomes somewhat less interesting; however, it does (somehow) lead to the Berkana-esque question: Isn't it odd that the words "organization" and "organic" have the same root? Doubters like myself can verify right here the etymological network connecting "organization" with "organic." The root is the Greek organon, literally "that with which one works," and which since the 12th century has described not only tools but also musical instruments and body parts.

Putting all our quotes and equations together, we have:

"Science is knowing tools, musical instruments, and body parts. Wisdom is living tools, musical instruments, and body parts."

And that, dear reader, is an org chart that really counts.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Pros and Cons of Male Enhancement

2008-07-30T06:54:00.003-04:00

Just in time for my last installment on network centrality, I have learned that Google now ranks Connectedness the #1 site on the Web for "pros and cons of male enhancement." It's tempting to take credit and say that this honor was the result of long, hard work on my part; but it was endowed upon me more by the fates of centrality than by anything I did. (Those who doubt my boast and are not afraid to look, click here: http://www.google.com/search?q=pros+and+cons+of+male+enhancement.)

Without taking anything away from the experts who have filled my blog with their thoughts on the topic, I now want to make perfectly clear my position on male enhancement: The field of collective leadership needs it bad, especially the non-profit/social-change sector.

I love working with collective leadership programs, and I am fortunate to do so regularly. The recipe for this work adapts to the participants, but it almost always involves something like the picture at right. See W.K. Kellogg Foundation's Collective Leadership Framework and the D.C. Leadership Learning Community's Nature of Collective Leadership for more.

In other sectors, collective leadership draws less with crayons and uses other more dangerous sticks. Speaking of collective leadership in the field of science, John Ziman says that each individual's contribution is "merely a tiny tentative step forward, through the jungles of ignorance." I don't think his savage choice of setting --- where only the fittest survive, thanks to teeth, claws, and other weapons --- was any accident.

My Introduction to Web Programming class has filled up again for this fall. It's my personal collective leadership learning lab. How can I equip 75 computer-illiterate college kids with the wherewithal to make their own websites (like these)? I can't. But together, they can. I facilitate my students' learning by dropping them into the Internet jungle and encouraging them to trust their own most primitive hacking instincts.

In the spirit of crayons and group hugs, my first gift to my students each term is an online discussion forum where they are encouraged to share anything relevant to the class. Speaking to a ballroom-full of faculty about his experience, Will Mundel noted first and foremost that "Thanks to the online forum we used in CS-103, students stop being individuals in a class. Rather, they are all in it together."

I am honored by Will's comment, but that's not the whole story of how my students learn to build their own websites. Underlying the experience of the class is a curriculum I have modeled on the traditional male rite of passage: (1) Throw a boy out of society into the wilderness; (2) Let him suffer and learn; and (3) Welcome the transformed man back into society. (That's my paraphrasing. Here's what the American Psychological Association says about this method of transformational learning.) If you look closely at this gallery of student projects, you'll see a quote from another student that speaks directly to her painful but ultimately victorious journey alone through the wilderness.

After subjecting my students to this webified passage of suffering, I top it off with a month-long tournament of hand-to-hand combat. Within the cage of this special-built wiki, the students compete for Google-rank supremacy. This part of the class evolved from my desire to translate the inner workings of the Google centrality algorithm into the real-life experience of the kids.

Inviting students into this kind of centrality-based competition is not easy. My first attempt provoked class revolt because students perceived the rankings as an unfair system of grading their work. (The fact that the competition had no impact on actual grades was irrelevant to this revolt.) My second attempt went smoothly: I was careful to provide a fair system for peer reviews in parallel with the same centrality-based competition. With fair peer reviews in hand, the students no longer were bothered by the arbitrariness of centrality rankings.

Last spring was my third and by far most successful use of the centrality competition. Not only was there no resentment at the arbitrariness of centrality rankings, but there was a positive embracing of the system. Students discovered how to form alliances and deliberately manipulate the Google algorithm into boosting their own rankings. A flurry of new links and surprise defections preceded the day of our awards ceremony. Three alliances shared top honors. When I refused to award a prize to one of the alliances because their team leader had skipped class that day, his teammates/co-conspirators texted him and made him show up, 20 minutes late, so that they could receive their prize: a one-half of one percent boost in final course grade.

Technical postscript: For those wondering how it's possible to share top honors in a Google centrality competition, the answer is quite technical. From this more-or-less readable description of the Google algorithm, you can discover a "damping factor" that Google does not allow users to see or edit. I provide my students with a Google centrality calculator that allows them to edit this damping factor to whatever they want. Changing the damping factor can sometimes change the winner of the rankings; I award first prize to anyone who can find a damping factor value that puts them atop the rankings. In the following network, every single node with a label can win the Google centrality contest with the right damping factor:

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Making us Lazy Conformists, Says NSF

2008-07-18T16:55:00.000-04:00

[Ed note: This is the last tangent before we really finally close the network centrality thread with a positive note, coming soon.]

The NSF reports today: "The Internet gives scientists and researchers instant access to an astonishing number of academic journals. So what is the impact of having such a wealth of information at their fingertips? The answer, according to new research released today in the journal Science, is surprising--scholars are actually citing fewer papers in their own work, and the papers they do cite tend to be more recent publications. This trend may be limiting the creation of new ideas and theories."

This is an argument for Google-induced stupidity that I can agree with (unlike last week's).

My only beef with the NSF blurb is the notion that anything "surprising" is happening here. There is plenty of evidence of our lemming-like ways in other contexts; we should expect a human tendency to dive over the cliff of the web's dark side. Here's a first-person demonstration. By doing a bit of Googling I can share the first decent link that pops up to support the claim that humans are lemmings: Conversation, Information, and Herd Behavior, in the American Economic Review, 1995. Using Google in this way, I can feel myself regressing into a rodent even now.

One of the first, most famous and shocking demonstrations of human lemmingness was devised by Solomon Asch in the 1950's. Most people after reading this story find it hard to believe that it could happen to them. I had the "good fortune" to be tricked by my college psychology professor into Asch's trap, exposing my irrational lemmingness for all my 200 classmates to see. I have no doubt that I am a weak-willed conformist.

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Network Centrality: Making Us Stupid, Says Atlantic Monthly

2008-06-30T13:41:00.000-04:00

"Is Google Making Us Stupid?" asks Nicholas Carr on the cover of this month's Atlantic Monthly. In a nutshell, Carr laments the decline of "deep reading" and suspects that we are losing "deep thinking" as well. I would not argue the "deep reading" point, but the connection to "deep thinking" is debatable and surely this excellent rebuttal is not the last blog post that will take Carr to task.

Here I will argue Carr on a different point. About two-thirds into his essay, he says:

"Sergey Brin and Larry Page, the men who founded Google, speak frequently of their desire to turn their search engine into an artificial intelligence. 'The ultimate search engine is something as smart as people—or smarter,' Page said in a speech a few years back. 'For us, working on search is a way to work on artificial intelligence.' In a 2004 interview with Newsweek, Brin said, 'Certainly if you had all the world’s information directly attached to your brain, or an artificial brain that was smarter than your brain, you’d be better off.' ....

[Carr continues] "Such an ambition is a natural one, even an admirable one, for a pair of math whizzes with vast quantities of cash at their disposal and a small army of computer scientists in their employ.... Still, their easy assumption that we’d all 'be better off' if our brains were supplemented, or even replaced, by an artificial intelligence is unsettling. It suggests a belief that intelligence is the output of a mechanical process, a series of discrete steps that can be isolated, measured, and optimized."

Two counterarguments immediately come to mind in response to the above:

For many of us, it is quite natural to believe that intelligence can be the output of a mechanical process. I suspect I am in a minority on this point, so for those who are curious to consider intelligence outside the stuff of brains, I simply recommend the book, The Mind's Eye, a collection of essays around this topic edited by Douglas Hofstadter and Daniel Dennett.
In the passage above, there is a belief espoused explicitly by Brin and implicitly by Carr that is even more unsettling (at least to me) than the notion of mechanized intelligence: That we'd be "better off" if we were smarter. Read Carr's entire essay and you'll see that, just like his essay title suggests, he is very pro-smart and anti-dumb. I'll grant that with more intelligence, we have a way to boast of being "better than..."; but being "better off" is another question altogether.

In short, Carr's passion for intelligence combined with his strict accounting of its boundaries are a recipe for fundamentalism.

...

My regular readers may be wondering what happened to the "celebration of competitiveness" that I promised last time. Or maybe, what does any of this have to do with networks? Good questions. I beg your patience, dear reader-- I just could not resist this tangent, and I promise to celebrate centrality, measurement, and competitiveness soon. Meanwhile, I close with this chapter from the Tao Te Ching, which comments on the consequences of increasing intelligence:

Network Centrality: More Current Events

2008-06-23T08:04:00.000-04:00

Last week we kicked off our "Separation of Network Power" series in honor of the June 12 Supreme Court ruling on hearings for Guantanamo Bay detainees.

This week we'll continue the series, inspired by Congressional action of June 19 to let the White House and phone companies off the hook for warrantless tapping of domestic US communications since 2001.

Showing how far one branch of government can implicitly subjugate itself to another, Congressional Democrats claimed victory for including a special clause in the law that prohibits the White House from breaking it. In the words of the NY Times:

The most important [White House] concession that Democratic leaders claimed was an affirmation that the intelligence restrictions were the “exclusive” means for the executive branch to conduct wiretapping operations in terrorism and espionage cases. Speaker Nancy Pelosi had insisted on that element, and Democratic staff members asserted that the language would prevent Mr. Bush, or any future president, from circumventing the law. The proposal asserts “that the law is the exclusive authority and not the whim of the president of the United States,” Ms. Pelosi said.
In the wiretapping program approved by Mr. Bush after the Sept. 11 attacks, the White House asserted that the president had the constitutional authority to act outside the courts in allowing the National Security Agency to focus on the international communications of Americans with suspected ties to terrorists and that Congress had implicitly authorized that power when it voted to use military force against Al Qaeda.

Network centrality and the executive branch make for tough competitors in the struggle not only to separate but also to balance the powers of the collective. Last time I lamented the dark side of centrality and competition. Next time I'll celebrate the good side.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Size Does Matter

2008-06-20T15:39:00.000-04:00

Today, the summer solstice, ranks with sunrises and full moons as one of the original inspirations to human time-telling and measurement. Here is a a classic New Yorker cartoon showing what that moment might have looked like.

We have come a long way since then. As recounted by author Dava Sobel, our ability to measure time with precision turned out to be the final critical breakthrough that enabled us to navigate across oceans, rather than simply drift and hope for a safe harbor to appear on the horizon. As the cartoon attests, however, we paid a high psychological price for this ticket to global connectedness. We measure time not just to travel over the horizon but also to worry about getting there soon enough.

So it is with network centrality. No matter what kind of network centrality catches your fancy, it can both empower you to navigate farther and more accurately across great "distances," and it can nag you with the question of how well you measure up.

One big difference between time and centrality is that unlike time, which rests on rhythms of nature (earth, moon, sun, cesium atoms, etc), centrality is a mathematical abstraction with a maddeningly circular non-grounding in reality. In other words, when it comes to centrality, "perception is reality." Martin Kilduff and David Krackhardt argue this much more rigorously in their Analysis of the Internal Market for Reputation in Organizations, which states: "We found that being perceived to have a prominent friend boosted reputation, but that actually having such a friend had no effect." The implications of this result for the practice of ONA consulting could not be more profound.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: All Your Links Are Belong to Us

2008-06-19T12:09:00.000-04:00

Yesterday was a full moon. Tomorrow is the longest day of the year. What better day to celebrate the brightest metric known to network science: centrality.

Connectedness celebrates centrality by putting Google, the world's most popular centrality-based tool, to work. For any set of keywords you can imagine, Google points you to the center of that universe. Each link below does exactly that, using the highlighted text as the keywords. Results are real-time and may change after this post goes to press.

Network Centrality: The center of this universe is Steve Borgatti. Yeah!
Organizational Network: The center of this universe is Valdis Krebs. Kudos to you, Valdis. I am jealous.
Community Network: Apparently centered in Seattle. Interesting. How did Seattle beat out Portland, OR?
Collaboration, Innovation: Centered on Dave Pollard. This confirms my excellent impression of him from a couple months ago--which was the first I heard of him.
Leadership, and most other words you care to look up: Wikipedia has the first answer you will find.

No celebration of centrality would be complete without asking, "What universe am I the center of?" For Connectedness, the answer is: sears refrigerator customer service repairman. To all my readers, let me say: Welcome to the inner sanctum.

While you're celebrating having "arrived," let me add that this weekend is the fourth birthday of Connectedness. All the more reason for jubilation.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Holy Trinity of Network Power

2008-06-16T09:21:00.001-04:00

Last Thursday the US Supreme Court ruled that prisoners at Guantanamo Bay have a right to hear and to challenge the reasons for their detention.

Eric M. Freedman, a habeas corpus expert at Hofstra University Law School, called the decision "a structural reaffirmation of what the rule of law means," and said it was as important a ruling on the separation of powers as the Supreme Court has ever issued, according to the NY Times.

Dating back at least to ancient Greeks, the separation of powers traditionally splits state power into three parts: executive, legislative, and judicial.

Over the next few posts, Connectedness will celebrate the separation of powers by comparing each of its three components to three notable pillars of the network perspective: centrality, clustering, and structural equivalence.

Stay tuned for something like this:

Politics	Networks	Easy-to-Remember Stereotype
Executive	Centrality	Tyrannical Dictator
Legislative	Clustering	Mob of Special Interests
Judicial	Structural Equivalence	Politically Unaccountable Intelligentsia

Hopefully by July 4th, we'll have celebrated all three.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Fathers of Connectedness

2008-06-12T07:44:00.002-04:00

This Sunday is Father's Day. Here's a great picture of my dad growing up in St. Louis (far right, age 9):
My dad is first on the list of Fathers of Connectedness, naturally, because he's my dad. But he's also first on the list because his gift for letters and sense of humor inspired my own love of writing, which is the main reason Connectedness continues to exist.

My grandfather (wearing the tie) is next after my dad. He was a shoe salesman, but in that seemingly common role he had the singular opportunity to tour the country with Robert Wadlow, the tallest human being who ever lived. (Presumably Mr. Wadlow also wore the biggest pair of shoes ever cobbled.) Kudos to Grandpa for his marketing savvy, a quality I strive for with each post to this blog.

On my mother's side of the family, two more fathers have clear ties to Connectedness. My mother's father, Alan Foust, is the source of my inner engineer. He co-founded the Department of Chemical Engineering at Lehigh University, later served the College as Dean, and is the one grandparent I knew best. I was too young to appreciate his academic stature at the time, but I certainly understood his inexhaustible energy for explaining things. Whenever people wonder how I can go on and on about the same thing --long after the original question is answered-- that's me and my Grandpop doing our thing.

My mother's mother's father (aka my great-grandfather) was also a professor: Ralph W. Aigler. I never knew him at all, but he is certainly my most famous relative. Someone on Wikipedia really thinks he is famous, anyway. My favorite parts from the Wikipedia article include:

Ralph W. Aigler, law professor at the University of Michigan from 1910–1954, was a renowned expert on real property law and one of the advisors to the American Law Institute in the drafting of the Restatement of the Law of Property.

He is best known, however, for his contributions to the athletics programs at the University of Michigan. Aigler's contributions included leading Michigan back into the Big Ten Conference, leading the effort to construct Michigan Stadium, and negotiating the Big Ten's exclusive contract with the Rose Bowl starting in 1946. He was inducted into the University of Michigan Athletic Hall of Honor in 1982.

Aigler was the voice of the University, and at times of the Big Ten, on athletics eligibility and rules issues. In 1925, Aigler defended intercollegiate athletics against charges that they had a negative effect on institutions of higher learning. Aigler said that the harm done by athletics was almost nothing when compared to the evils caused by "common loafing." "The greatest vice in American college life today is loafing," said Aigler. "There is no doubt that this far overshadows the harm created by intercollegiate athletics. No one would be more pleased than I to see a Phi Beta Kappa (honorary scholarship society) man receive as much recognition by the public as do our leading athletes. But such a condition would be contrary to human nature. Intellectual attainments do not make such an appeal, and that is why athletics are so prominent in colleges and universities today."

It's great to hear voices from the intellectual mountaintop offering humble encouragement to regular human nature.

Speaking of regular human nature... The Wikipedia article on Great-Grandfather Aigler omits the part of his life story I know best. When he was 58, his wife died of breast cancer. When he remarried at the age of 60, his new wife was 27 (5 years younger than her new step-daughter, aka my grandmother). Here are the newlyweds, enjoying the beginning of their 19-year happy affair that lasted until his death at 79.

Thanks, Dad! And thanks, all my other fathers!
Love, Bruce

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Cell phone spying, physics, and ethics

2008-06-06T15:54:00.001-04:00

Laszlo Barabasi, network maven and author of Linked, has moved to Boston, where he now directs the Center for Complex Network Research at Northeastern University (CCNR). Yesterday, the Center made headlines around the world after announcing that they had tracked the whereabouts of 100,000 cell phone users. The subjects of this experiment did not know they were being followed non-stop for 6 months.

The BBC headline was "Mobile phones expose human habits," which generated this post from Raph Koster, noting that the main technical result of the study (related to the "power law") is hardly as surprising as the researchers claim. (See Shirky for more on power laws; and if you really want to know, see Mark Neuman's scholarly explanation of why they pop up everywhere.)

American news coverage slanted away from the technical findings of the study and focused more on its dubious ethics. The passages below are from this this Reuters story published by the New York Times, and from yesterday's Boston Globe:

"Researchers who spied on 100,000 people using their cell phone signals confirmed on Wednesday that most human beings are indeed creatures of habit."

"The first-of-its-kind study by Northeastern University raises privacy and ethical questions for its monitoring methods, which would be illegal in the United States."

"'This is a new step for science,' said study co-author Albert-Lazlo Barabasi, director of Northeastern's Center for Complex Network Research. 'For the first time we have a chance to really objectively follow certain aspects of human behavior.'"

"Barabasi said he spent nearly half his time on the study worrying about privacy issues.... Barabasi said he did not check with any ethics panel. [Barabasi's co-author] Hidalgo said they were not required to do so because the experiment involved physics, not biology. However, had they done so, they might have gotten an earful, suggested bioethicist Arthur Caplan at the University of Pennsylvania."

I am confused about a couple things here. Is "physics" the most appropriate name we have for the science of observing human habits and movement? And even more importantly, what does it mean that physics experiments do not need oversight by an ethics panel?

I am also sad to see that the URL for the Center for Complex Network Research at Northeastern University is http://www.barabasilab.com/

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Ownership and the Power of Networks

2008-06-03T11:17:00.003-04:00

An invitation to learn about "The Power of Human Networks®" crossed my desk recently. There's still time for you to join the webinar hosted by HR.com and featuring Myra Norton of Community Analytics among others.

I was fascinated to learn that Community Analytics now owns a registered trademark for "The Power of Human Networks®". Thank goodness they don't have a patent on human networks, or I'd be out of business.

Networks by nature tend to blur ownership for the benefit of collective power, and registering a trademark is among the clearest ways to claim ownership and thereby increase individual power. Wow! Fascinated by the interplay of these three concepts, I searched the US Patent and Trademark Office database to see who else owns a stake in "power" and "networks". The owners of these trademarks are surprisingly few. One is TheSquare.com, whose CEO owns "The Power of Your Network. Squared®". Hardly a threat to Community Analytics. The only real competition I see in the trademark archives is "Strategic Power Networks®", which is owned by strategic futurist Mary O’Hara-Devereaux, whose firm Global Foresight helps clients "Get to the future... Fast."

No review of "network" trademarks ("power"-ful or otherwise) would be complete without a bow to Sun Microsystems, which registered "The Network Is the Computer®" back in 1996. The slogan is only more powerful 12 years later. Sometimes I wonder if Sun got to the future a bit too fast with its slogan. Network power, just like a good joke, requires a talent for timing.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Chain mail and effective flow

2008-05-19T12:21:00.000-04:00

Network uber-guru Jon Kleinberg made headlines again this week: "Boffins question spread of email chain letters."

Before the newspaper headlines crossed my desk, Nathan Gilliatt at The Net-Savvy Executive saw the original paper in the Proceedings of the National Academy of Sciences. Gilliatt sums it up:

"A study published by the (US) National Academy of Sciences demonstrates that email, at least, follows a meandering path to large audiences, rather than a short path via online influencers. Tracing information flow on a global scale using Internet chain-letter data, by David Liben-Nowell and Jon Kleinberg (via IntelFusion). The choice of email as the channel guarantees the deep and narrow result."

Gilliatt goes on: "The more interesting question—and the more challenging—is to track the spread of information and opinions across the many channels people use, both online and offline. .... Picture water flowing downhill. If there's a wide channel available, water will use it. If there's a narrow channel, it will use that. Where both are available, it uses both. Information works the same way. The key is that water wants to flow downhill. To make this work with ideas, you need ideas that people want to communicate."

I like Gilliatt's take, but I am frustrated how terms like "deep and narrow," much like "strong tie" and "weak tie," are so weighted with multiple cultural interpretations that it's pretty much impossible to quote Kleinberg's use of "deep and narrow" without distorting his point.

My favorite part of Gilliat's post is his "more interesting question" and his watery metaphorical conclusion. Kleinberg speaks to this in his own way as well. In this 3-minute NSF video/interview, he concludes by saying that the broader implications of his research are "how to make the spread of news more effective," and "how to make public discourse and participation more effective."

To me, the even more interesting question is, "What is 'more effective' as it applies to news and public discourse & participation?" I would love to hear Rupert Murdoch's answer to that question. I also wonder what a poll of net-savvy executives would reveal. Gilliatt's watery closing invites us to reflect on another expert on effective flow, Lao Tsu:

Competent Jerks and Lovable Fools, Part 2

2008-05-14T11:40:00.001-04:00

After an all-day grading marathon yesterday, today I am ready to file grades for the semester. No fun. But there were plenty of fun moments this term to make the pain of grading worthwhile. One of my favorites was this response to an exam question:
The student who wrote this never did any reading and forgot to submit almost half of his homeworks. But he was one of the most active participants in class--never missing an opportunity to turn my chalkboard networks into jokes that made the learning fun for all. How can a teacher reward the contributions of such a student? Certainly not with the grade I am giving him.

The title of this post refers back to an HBR story I reviewed: Competent Jerks and Lovable Fools. Now I also want to rehabilitate the notion of "fools": those jokers who are not foolish at all, but instead speak the wisest truths. It's a Shakespearean tradition and a quite a treat to encounter in real life.

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Claire Reinelt and Evaluation of Leadership Networks

2008-05-02T14:21:00.003-04:00

Claire Reinelt is Director of Research and Evaluation at the Leadership Learning Community. We spent the last few months distilling our experience into a paper that we just submitted to Kelly Hannum and Bart Craig, who are guest editing a special issue of The Leadership Quarterly on Evaluation of Leadership Development. We are grateful to them for permitting us to share our manuscript.

Social Network Analysis and the Evaluation of Leadership Networks
By Bruce Hoppe and Claire Reinelt

PDF of article available here

Abstract
Leadership development practitioners have become increasingly interested in the formation of leadership networks as a way to sustain and strengthen relationships among leaders within and across organizations, communities, and systems. This paper offers a framework for conceptualizing different types of leadership networks and identifies the outcomes that are typically associated with each type of network. One of the challenges for the field of leadership development has been how to evaluate leadership networks. Social Network Analysis (SNA) is a promising evaluation approach that uses mathematics and visualization to represent the structure of relationships between people, organizations, sectors, silos, communities and other entities within a larger system. Core social network concepts are introduced and explained to illuminate the value of SNA as an evaluation and program tool.

Introduction
Leaders need effective and efficient ways to connect with one another to share information, get support, mobilize resources, learn, and align their visions in a strategic direction. Often leadership networks form (or are created) to make it easier for leaders to connect. Leadership networks form in different ways. Sometimes networks form as the result of an intentional selection process. Many leadership programs bring together diverse participants who normally would not interact: for example, professionals who work in different fields or sectors; or business and civic leaders in a community. In these programs, they have an opportunity to get to know each other, share their experiences and perspectives, and form bonds that may endure over time. While individuals who participate in programs always have the chance to keep up individually with each other, organized network activities such as listservs, retreats, and learning communities can nurture those relationships both face-to-face and online.

Other leadership networks form through a process of collective emergence (Johnson, 2001). These networks are typically more complex and capable of reaching a larger scale. They have self-organizing processes that leaders participate in out of self-interest, shared values and/or a sense of collective purpose. These leaders communicate and engage in actions that are self-directed and facilitated by ties in the network. An example of an emergent network is Amazon.com where people purchase and review books. These activities create a large amount of information that is highly valuable to someone new who is considering purchasing a book. An emergent leadership network occurs when individuals and organizations come together around a shared purpose or cause. By acting together they have a collective power that is not possible if they remain fragmented and isolated.

One of the challenges for the field of leadership development is how to evaluate leadership networks. How does one visualize, analyze, and understand the relationships among leaders? What are the boundaries of a leadership network? What are the currencies (e.g., information, resources, etc.) that flow within networks? How can a network be strengthened? Can networks be mobilized for social and systems change?

In this paper we provide a framework for understanding different types of leadership networks, and consider how social network analysis can be used as a tool for evaluating leadership networks.

We distinguish four types of leadership networks:

Peer leadership networks
Organizational leadership networks
Field/policy leadership networks (sometimes called “production networks”)
Collective leadership networks

Each of these networks can be characterized by who participates in the network, what circulates through the network (e.g., information, expertise, resources), what binds people together, and what they do for and with each other. We discuss each network type and provide examples for each. We also identify outcomes that are commonly associated with each type of network and how participants in different types of networks are using social network analysis. Interspersed throughout the paper are discussions of three methods of network assessment: connectivity, centrality and structural equivalence. We end the paper with a discussion of network visualization, the ethics of collecting and interpreting network data, and some of the most promising uses of network data for leadership development purposes.

PDF of article available here

Learning and loving? at BU

2008-05-01T17:50:00.000-04:00

Classes ended today at BU. I am exhausted. Somewhere mid-Fall I got hooked by my own material and ended up deep in my head for most of the next six months.

Now I am seemingly returning to earth, slowly.

Along the way, I noticed this spectacular final project of Kristyn Ulanday, one of my students. It features this quote by Dorothea Lange:

"While there is perhaps a province in which the photograph can tell us nothing more than what we see with our own eyes, there is another in which it proves to us how little our eyes permit us to see."

That's sort of how I feel about words these days.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Knowing the path and walking the path

2008-04-25T09:49:00.001-04:00

One of the great and tragic lessons of my life so far is that the ability to distinguish four major categories of network centrality and code them all in an Excel spreadsheet does not, in and of itself, bring me the ladies. Denial, anger, depression--somewhere amidst these precursors to acceptance comes a revelation. Perhaps network centrality will show me who is getting the ladies, so that I can learn from them, or, failing that, construct an argument demonstrating some measure by which I am superior to them.

Looking at the network of sexual relationships among Jefferson High School students (which I mentioned last time), it doesn't take a PhD to see that these kids spend plenty of time away from their spreadsheets:
No matter how liberal I am, surely my desire for public health must respond to the above network. Measures of connectivity and centrality impel me to have a talk with the "key players" of the sex network. Their reproductive health (and the health of many of their classmates) depends on it. Yes?

Actually, no. This teenage sex network does make a great emotional appeal: hire a network analyst so that you can target key players in your advocacy campaign. However, the central point made by authors of the above map, over the course of 40 pages, is exactly the opposite:

"Epidemiologists, unable to observe or measure directly the structure of sexual networks, have tended to latch onto a single idea: specifically, the idea that the number of partners matters for STD diffusion dynamics.... Our data suggest that a shift in social policy toward comprehensive STD education for all adolescents, not just those at highest risk, would be significantly more effective than current intervention models."

In other words, when it comes to teenage sex, don't waste any time targeting key players in the network. The teenage sex network, by its very nature, tends to connect in a way that makes the very notion of "key player" irrelevant. So concludes the paper "Chains of Affection" by Bearman, Moody, and Stovel.

Not all networks connect in this way. Sometimes it does pay to hire a network analyst and target key players in your advocacy campaign. Specifically, if Bob and Alice complete the partner-swap we see here (and others do likewise), then my services are definitely called for.

Kids turn out to be better than adults at avoiding these sorts of messes.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

10 Minutes for Marty Kearns of Netcentric Campaigns

2008-04-15T13:44:00.000-04:00

Last week I enjoyed a presentation by Marty Kearns of Netcentric Campaigns and Green Media Toolshed. My big take-away was the notion of the 10-minute volunteer: if someone shows up willing to help me for 10 minutes, and will just as surely forget about me in 11 minutes, how can I make use of this gift? Most people would rather ignore such a flighty volunteer, but Marty makes a great case for bringing them in, just for those 10 minutes. For example, "Where are they now?" runs a massively distributed phone campaign to expose dubious staffer moves within Congress.

OK my 10 minutes is up. Coming soon--a closer look at the (in)famous sexual relationship network of Jefferson High School, which Marty used as part of his introduction:

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KM 0.0 by Dave Pollard

2008-04-03T06:47:00.000-04:00

Recently I was invited by HP's knowledge management (KM) connector Stan Garfield to join a conference call that featured Dave Pollard. It was the first I heard the expression "KM 0.0", which was perhaps coined by Dave here. Dave describes KM 1.0 as "content and collection," and KM 0.0 as "context and connection." This not only makes for a poetic KM checklist, but it also reminds us that the better we get at KM, the more our KM draws from pre-historic roots of humanity.

My attempt in the conference call to agree with Dave did not get very far. Too many ideas in my head and not enough sense out of my mouth, I think. Nevertheless, those who want to support Dave's "KM 0.0" notion will do well to notice how 1920's anthropological study of archaic societies anticipates this 2006 MIT Sloan Management Review cover on "Enterprise 2.0."

Dave's poem also deserves more consideration:

Content, collection;
Context, connection.

I interpret this poem as a tribute to Amazon.com and other exemplars of the Long Tail phenomenon--digital hosts who provide not only content but also ways for users to interact through their experience of that content. It's an amazingly successful network recipe cooked with equal measures of centrality, clustering, and structural equivalence.

Too many ideas in my head now, so I must sign off.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Please share with me so that I can beat you

2008-02-12T08:45:00.000-05:00

[Ed note: The Connectedness staff is behind in blogging, due to an overload of Web Science synthesis. We apologize for any inconvenience this may cause.]

Martin Nowak is one of the world's pre-eminent gurus of evolutionary dynamics (which I called "die and adapt" a few months ago). Yesterday at the Harvard Kennedy School Complexity Series, Nowak brilliantly outlined five reasons why I might willingly die so that you can live, and and what adaptations occur in our population as a result:

Kin selection: you are genetically similar enough to me (e.g., child, sibling) that I could rationally decide to sacrifice my own body for the sake of helping your/my DNA
Direct reciprocity: you and I interact repeatedly, and I expect that over time you will repay the favors I give you now
Indirect reciprocity: I may never see you again, but I care about my reputation (and know about yours), and I gain enough in reputation to make it worth doing you a favor.

The above three mechanisms of cooperations were rounded out by two more: graph selection and group selection, which allow one to model (1) a world where people don't randomly mix with the entire world but instead have specific neighborhoods of interaction, and (2) a world where tribes develop collective strategies. This last one (group selection) is still somewhat controversial, and Nowak himself has flip-flopped over the course of his career with respect to it. Currently he believes it is an important dimension of a complete model of the evolution of cooperation.

The talk and audience were theoretical-minded, but the person sitting on my right shared a very pragmatic reason for attending:

"The successful push-pull of collaboration and competition ... [in] both open source programming and wikis and is certain to find its way into many enterprises as collaborative design becomes commonplace."

More about that in his paper, "In Praise of Tweaking," where he makes clear one specific enterprise that is deliberately investing in theoretical evolutionary dynamics in order to redesign its own process of production. Thank you, Ned Gulley.

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Economic externalities and network science

2008-01-10T06:59:00.000-05:00

Thanks to Six Degrees: The Science of a Connected Age, which I use as the textbook for my course on web science, I have learned about economic externalities. I don't always include the topic of economic externalities in the class, but last fall I did--with intriguing results. It was all part of the major course redesign that preoccupied me more or less 24/7 from Columbus Day until Kwanza.

Here are the four types of economic externalities according to Duncan Watts, with explanations and examples by yours truly:

Information externalities: Knowing how others have acted under similar circumstances saves me the effort of evaluating all the options "objectively." Example: I am hungry. McDonalds has sold 30 billion Big Macs. They must be OK.
Coercive externalities: Anticipating the impact of my decision on others influences my choice. Example: Everyone is drinking at this party. What will they think of me if I don't drink?
Market externalities: As a particular option is chosen by more and more people, that option becomes more and more valuable to all those who have chosen it. Example: In 1980 very few people had email and so email was of very limited use. In 2007 many people have email and that popularity makes email exponentially more useful.
Coordination externalities: I will sacrifice my short-term selfish interests for long-term gains that depend on favors from others, to the extent that (1) I care about the future, and (2) I believe my actions affect the decisions of others. Example: When my friend lends me $10, I will pay him back the next time I see him. I lose $10 when I pay him back but gain more than that in the long run.

Watts discusses the above concepts almost exclusively in terms of their relationship to "tipping point" network dynamics. He also emphasizes the top of the list at the expense of the bottom. Having swallowed Watts' taxonomy of economic externalities into the same pipeline that is slowly digesting Tim Berners-Lee's framework for web science, I now have (1) a chronic case of indigestion, and (2) the following mapping of economic externalities onto basic concepts of network science:

Information externalities --> cardinality and centrality
Coercive externalities --> connectivity and clustering
Market externalities --> structural equivalence
Coordination externalities --> symmetry and asymmetry

As I prepare for spring '08, the above appears to be the backbone of my web science curriculum. If it doesn't make sense, dear reader, please be patient with me and stay tuned!

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Performance reviews

2008-01-02T15:33:00.000-05:00

Now that grading is done, I get to see my fall student evaluations. I skimmed a handful earlier today and spotted a few "five-star" marks and a couple stinging criticisms. Time to pause now. The forms are resting outside in my car, so that tomorrow I can bring them inside and absorb them with an appropriately cool frame of mind.

The very same day my students wrote their anonymous evaluations, they handed in their final project reports. Each student had the entire semester to build any kind of website she wanted (e.g., Japanese, business, entertainment, sports, travel, cars). Each final project report told the story behind the website, concluding with the most valued lessons the student learned over the course of the project. One of my favorite endings was this:

I had, before this class, become obsessed with learning code "hardcore", but I see that I'll pretty much always be able to find useful code snippets in resources online.... For coding a whole website, it's not so much about a limitless knowledge of code, but about persistence. With trial and error, focus, solid consideration, and just a little work, you can usually make what you envision a reality (or something that works just as well as what you'd envisioned).

Cool!

The flip side of this lesson came out in the anonymous evaluations. (Written the same day.) One student said it simply: "Everything I learned I had to teach myself." Another said, "Sometimes it seemed like there were students who knew more than the instructor." In the context of my consulting work, those two quotes could very easily be compliments, but my students wrote them in response to the question, "What were the most significant weaknesses of this course?"

My impulse in these moments of paradox is WWLTD -- "What Would Lao Tsu Do?" I am not sure that Lao Tsu's paycheck depended on anonymous student evaluations, though.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Delete all your links, except to me

2007-12-05T07:19:00.000-05:00

As part of the course re-design I mentioned last time, I have been digesting this excellent summary of Google PageRank that my students found for me a few weeks ago. I have boiled it down to this. Another way I teach my students PageRank is by entering all their semester web-programming projects into a PageRank contest, where the PageRank is determined by student recommendations entered into our class wiki.

The contest has one more week to go. You can see the front-runners vying for votes (or not) in the wiki excerpt below. They are listed in order of PageRank:

Site Link / Description	Incoming Links
http://people.bu.edu/gatewood/index.html Quit editing this wiki, get out and do something! My site is a December calendar of events, from concerts to festivals, that would interest a college age student in Boston.	choy alliew rgm ajhlee jihong88 cohens11 xzhang08 dbrien lbdunn
http://people.bu.edu/afacini/gaijin/ A resource site for learning how to read and write basic Japanese. Learn to write both hiragana and katakana, the basic alphabet scripts of Japanese.	jasonhu gaep13 wcmundel icc arthim edflem yasmin89 kevshea slee0903 dan013 abg cnm lbdunn
http://www.tormor.org The homepage of me and a friend of mine and our upcoming vegetable oil fueled cross-continental adventure.	jasonhu alliew tjpirog billba edflem yuliyab cohens11 koates andrak lbdunn
http://people.bu.edu/xzhang08/psych/index.html Enjoy looking at optical illusions? This website has lots of optical illusions and explains how each works!	gaep13 gillianb arthim yasmin89 timwalsh ajhlee mgro27 slee0903 dbrien jfsr lbdunn
http://people.bu.edu/anishk/Kattukaran-Webproject/Index.html (Firefox recommended) A website for a startup company that i am working on. The new venture will deal with educational services targetted at students from developing countries and aims to improve the standards of education in many of these countries.	aecook gaep13 icc haysher edflem dechat eeun zucchig bross55 lbdunn eskizzle
http://people.bu.edu/ajhlee/cs103/index.html This page is about how hip hop is dead	jihong88 cohens11 gatewood eeun jfsr edflem lbdunn

My favorite feature of PageRank is this strategy suggested by the PageRank article: "Outbound links are a drain on a site's total PageRank... But there are 'abnormal' ways of linking to other sites that don't result in leaks. PageRank is leaked when Google recognizes a link to another site. The answer is to use links that Google doesn't recognize or count."

This is true enough. To dramatize the point, I have provided my class with an Excel spreadsheet that takes the above wiki table as a copy-and-paste and instantaneously provides the resulting PageRank scores and relative class rankings. Each student can edit the resulting spreadsheet and see exactly how much his score goes up when he deletes all his outbound links and stops recommending other students' websites.

Hopefully, by the time I do the final PageRank calculation, all my students will have taken this lesson to heart and deleted all their links. You should too. Boost your visibility on the Internet by deleting all outbound links from all your blogs and other sites--except links to me. Thanks!

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Experiencing technical difficulty--please stand by

2007-11-03T16:09:00.000-04:00

Major course redesign happening in front of a live student audience has Connectedness staff preoccupied. Regular blogging will resume shortly.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Use Visone to make your first network map

2007-10-12T07:41:00.000-04:00

I often get asked about network mapping software. I switch back and forth between several programs depending on what I want to do. For most, I usually recommend NetDraw. However, for those wishing to make very simple maps, another excellent choice is Visone.

You can easily run Visone with the "webstart" option available here. Once you have it running, the picture below hints at how easy it is to (1) give yourself a starting set of nodes by creating a "random" graph with no edges, and (2) use "edit mode" to make your nodes look as you wish and add edges between them. Then you can use "analysis mode" to drag nodes around and try different automatic layouts, etc.I use Visone to make all the illustrations in my Introduction to Network Mathematics, but I don't use it for consulting because it is licensed only for non-commercial use.

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Information advantage

2007-10-03T07:56:00.000-04:00

I attended a talk recently about computational sociology and data mining. The speaker began with a claim that technology is never policy-agnostic but almost always advocates for some policy or other.

Half-way through the talk, someone referred to the impressive array of technology employed by the speaker's research and asked what policy that technology was advocating. The speaker deftly avoided the question by raising policy questions without answering any of them. He was policy-agnostic, you might say.

In such situations (and many others), it is a safe bet that the policy being advocated by the technologist is "I deserve your respect, money, and/or votes."

The best case I have seen for this argument was put forth by Robert Thomas in his book, What Machines Can't Do, which I originally mentioned here with respect to user-driven innovation.

I agree with Thomas, and certainly hope that my blog wins me your respect, money, and/or votes. Let the world know how much you admire my wisdom and power:
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When nothing is done, nothing is left undone

2007-09-22T11:31:00.000-04:00

Bridging the gap between structuralist and individualist approaches to social networks

2007-09-20T08:08:00.000-04:00

My book report on Social Networks and Organizations, by Kilduff and Tsai. Part Four of a Series.

Chapter Four: Bridging the gap between structuralist and individualist approaches to social networks. Kilduff and Tsai shine an unflinching and highly amusing light on this seemingly religious rivalry--another good case study for Bion and Shirky.

This chapter, in my opinion, is the single best chapter of the book and all by itself justifies the book's $45 purchase price.

Kilduff and Tsai show us the soap opera of real science. In this episode, individualists have thrown down the gauntlet and decried "the tendency in network analysis towards 'overelaboration of technique and data and an accumulation of trivial results.' (Boissevain)"

In response, "Network researchers tend to be united in their adherence to ... the anti-categorical imperative. This imperative, 'rejects all attempts to explain human behavior ... in terms of categorical attributes of actors.' (Emirbayer)"

Kilduff and Tsai go on, "The typical start to any social network article often involves a ritualistic swipe at those who have previously focused on the attributes of individuals."

After showing us the soap opera, the authors conclude: "There is a pressing need for non-dogmatic research that explores issues concerning how individual differences in cognition and personality relate to the origins and formations of social networks."

Recommend further reading:

Kilduff, M. and Krackhardt, D. 1994. Bringing the individual back in: A structural analysis of the internal market for reputation in organizations. Academy of Management Journal, 37:87-108.

Krackhardt, D. and Kilduff, M. 1999. Whether close or far: Social distance effects on perceived balance in friendship networks. Journal of Personality and Social Psychology, 76:770-82.

Kumbasar, E.A., Romney, K. and Batchelder, W.H. 1994. Systematic biases in social perception. American Journal of Sociology, 100:477-505.

Mayhew, B.H. 1980. Structuralism versus individualism. Part 1: Shadow boxing in the dark. Social Forces, 59:335-75.

Mehra, A., Kilduff, M. and Brass, D.J. 2001. The social networks of high and low self-monitors: Implications for workplace performance. Administrative Science Quarterly, 35:121-46.

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I hate physicists; Barry Wellman is God

2007-09-14T10:50:00.000-04:00

I attended a talk recently that reminded me of the not-so-hidden rivalry between sociologists and physicists who study networks. Conveniently, my notepad that day was the backside of my printout of "A Group Is Its Own Worst Enemy" by Clay Shirky. In this brilliant essay, Shirky explains how group dynamics take hold quickly and then tend to lead participants into three deep behavioral ruts (quoted from Bion):

Find sex partners (ladies, see my email link in the right sidebar)
Identify and vilify external enemies (physicists)
Venerate religious idols (Barry Wellman)

Physicists, sociologists, and network gurus of all stripes engage in these behaviors as much as anyone.

For all its brilliance, Shirky's essay suffers major flaws. He argues that "learning from experience is the worst possible way to learn something." I refer readers to group behavior pattern #1 for my first counter-example to this bizarre claim. Shirky also says, "Prior to the Internet, the last technology that had any real effect on the way people sat down and talked together was the table." By my estimation, the table pre-dates literacy, and so Shirky is ranking broadband access as more significant to talking than both reading and writing. Does that sound right to you?

I hope that my readers will check out Shirky's highly stimulating essay and come back to Connectedness for when I argue that the very title of his essay, "A Group Is Its Own Worst Enemy," is as problematic as the above two quotes.

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Mapping all of science

2007-09-12T08:03:00.000-04:00

Back in 1939, J. D. Bernal prefaced his 500-page treatise "The Social Function of Science" with these words:

"Science has ceased to be the occupation of ... ingenious minds supported by wealthy patrons and has become an industry supported by large industrial monopolies and the state. Imperceptibly this has altered the character of science from an individual to a collective basis, and has enhanced the importance of apparatus and administration."

Add the above passage to my list of retorts to proclaimers of the "dawn of emergent collaboration." Then flip ahead with me 280 pages to the one picture in the book, ambitiously titled "The Organization of Science":
Click on the picture to see the full map.

The moment I saw this map it reminded me of Katy Borner's work at Indiana University, which is part of the traveling exhibit, "Places & Spaces: Mapping Science." This exhibit includes a "Map of Scientific Paradigms" by Boyack and Klavens:What important information about "Science" is communicated by these outstanding maps? There is no simple answer to this question. For me, the most important information a map can convey is a sense of which places are close together and which are far apart. Others design their network visualization tools based on different priorities (e.g., NetViz Nirvana by Shneiderman and Aris).

Geographic cartography is already complicated enough to be a science in its own right. Network cartography is at least as complicated, thanks in large part to its indifference to the triangle inequality--the most fundamental property that mathematicians usually require of anything that purports to measure "closeness" and "farness." (See "Identity and Search" in Science for more on the subtleties of social network distance.)

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A lesson in network visualization from John Maeda

2007-09-10T07:54:00.000-04:00

Yesterday's NY Times featured a striking network map as the cover art for its annual real estate magazine:
Even better, here is a slide show with MIT Media Lab's John Maeda telling how he came up with the design, which he originally conceived as "Google mappish Mondrian. Sort of Pollack meets Mondrian."

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Social networks and organizations: Critique of theoretical foundations

2007-09-05T07:07:00.000-04:00

My book report on Social Networks and Organizations, by Kilduff and Tsai. Part Three of a Series.

Chapter Three: Is There Social Network Theory? Kilduff and Tsai acknowledge this obtuse yet persistent question and explore the theoretical foundations of SNA.

Kilduff and Tsai lose me at this point in their book by being a bit too earnest in their treatment of this question. My objection to their earnestness has little to do with SNA and more to do with asking of anything, "Is this a method or a theory?" Using a favorite SNA metaphor to illustrate my point, imagine a serious conversation debating, "Is x-ray imaging a method or a theory?" This is a pragmatic question for academics deciding whether to grant PhDs and other awards to those working on x-rays. For the rest of us, who cares? I just want to know when x-rays are helpful and when they are not.

My personal favorite example of this sort of question is counting: "Is counting a method or a theory?" Most of us experience counting as a useful but humble technique, or method. But any fan of Georg Cantor can tell you that counting is also an extremely subtle realm of profound theory. Less mathematical readers may better identify with this example: "Is language a method or a theory?" If you're like me, this is a fuzzy question because we are equally bad at appreciating illiteracy (experiencing language as method) and Noam Chomsky (understanding language as theory).

I think one reason SNA battles the method vs theory question so hard is because its devotees are still trying to find a home. Just look again at this picture of "web science" by Tim Berners-Lee and you can see how this proposed paradigm has no single foundation from which to proclaim its theoretical rigor. To my eye, the picture has so many overlapping fields that it actually detracts from Berners-Lee's intention to create "web science."

At the end of this chapter, Kilduff and Tsai recommend further reading, including:

Burt, R.S. 1992. Structural holes: The social structure of competition. Cambridge, MA: Harvard University Press.

Granovetter, M. 1973. The strength of weak ties. American Journal of Sociology, 78: 1360-80.

Granovetter, M.S. 1985. Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91: 481-510.

Monge, P.R. and Contractor, N.S. 1999. Emergence of communication networks. In F.M. Jablin and L.I. Putnam (eds), The new handbook of organizational communication: Advances in theory, research, and methods, pp. 440-502. Thousand Oaks, CA: Sage.

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Adapt or die: what businesses can learn from science and nature

2007-08-30T08:27:00.000-04:00

I just got this invitation to an entrepreneurial networking dinner featuring the talk, "Adapt or die: what businesses can learn from science and nature."

"Adapt or die" made me uneasy, especially when presented as a lesson to be learned "from science and nature," and so I mulled it over long enough to come up with three different reasons to edit the title to "Die and adapt."

Nature: Generally speaking, adaptation occurs in a population of organisms, and death occurs in individual organisms. The science of evolution and natural selection is largely about the essential connection between these two phenomena: the death of organisms is a key driving force in the adaptation of populations. Hence, "Die and adapt."
Science A: Those intellectual smarty-pants in white lab coats are more often wrong than not, and the most common way the wrong ideas get weeded out is when the scientists who believe in them finally die. Then the younger smarty-pants who have slightly better ideas can finally publish, get tenure, and squash the even newer, smarter, generation of upstarts. This scientific soap-opera makes for a tragically hilarious read in Bill Bryson's "A Short History of Nearly Everything." Hence, "Die and adapt."
Science B: As John Ziman says, "The author [of scientific literature] presents an entirely false picture of his actual procedure of discovery. All the false starts, the mistakes, the unnecessary complications, are hidden; and a yarn, of preternatural prescience, precision and profit, is spun." Keith Sawyer explains the same truth in Group Genius: "Fail early, fail often, fail gloriously." Now just substitute "die" for "fail" to see why we must "Die and adapt."
Bonus reason from the world of organizational theory: "When losing is learning"

"Adapt or die"--sounds so true, but perhaps it is counterproductive to posit "adapt" and "die" as two alternatives between which we must choose.

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http://webmathematics.net

2007-08-29T08:28:00.000-04:00

One more week before classes start. In preparation, I am improving my online Introduction to Network Mathematics, which you will now find at http://webmathematics.net. Along the way I am learning how to be dangerous with Adobe Creative Suite 3 Web Premium, a massively juicy collection of software that I have acquired as a concession to my students, who generally consider set theory and eigenvectors to be dry.

With the URL "http://webmathematics.net," I am tipping my cap to Tim Berners-Lee and gang over at http://webscience.org. Their work can be summed up by the picture at right.

I plan to integrate their "Framework for Web Science" with my own course as much as I can. The fact that they are writing for fellow PhDs and I am teaching non-technical college freshman makes this integration non-trivial, to say the least.

Whenever I get discouraged by the gap I am trying to bridge with this integration, I find encouragement in the words of my new patron saint, John Ziman. The same John Ziman who wrote that "publication of fragments of scientific work may well have been the key event in the history of science" also said:

"In my view the gravest weakness in the organization of modern science is the lack of systematic exposition of the consensus at the stage between [scholarly] review article and the undergraduate textbook."

You can find the above quote in Ziman's 1968 monograph, Public Knowledge ("An Essay Concerning the Social Dimension of Science"), specifically in the chapter "Community and Communications."

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"Information, Communication, Knowledge" by John Ziman

2007-08-23T10:16:00.000-04:00

I just finished reading Group Genius by Keith Sawyer, and can't thank Robert Rasmussen of Lego Serious Play enough for recommending this book to me.

My favorite part of Group Genius is the gushing review on the back cover by management guru Ori Brafman (of Starfish and Spider network fame). Brafman says, "Sawyer has completely changed how I think about creativity."

That kind of review buys into the "big light bulb effect" that Sawyer devotes his entire book to dismantling. Instead of big ideas and big light bulbs, Sawyer explains that creativity in fact happens through slow, small, and collaborative steps.

Sawyer's enormous collection of endnotes does a great job of reinforcing his well-spun anecdotes with scholarly empirical research. Even so, I think he understates the degree to which his own book is but a well-packaged echo of work done long before.

Lewis Thomas, in his essay "On societies as organisms" (published in his best-selling 1974 book The Lives of a Cell) quotes John Ziman thus:

"The invention of a mechanism for the systematic publication of fragments of scientific work may well have been the key event in the history of modern science.... A typical scientific paper has never pretended to be more than another little piece in a larger jigsaw--not significant in itself but as an element in a grander scheme. This technique, of soliciting many modest contributions to the store of human knowledge, has been the secret of Western science since the seventeenth century, for it achieves a corporate, collective power that is far greater than one individual can exert."

John Ziman wrote those words in his essay, "Information, Communication, Knowledge," published by Nature in 1969. My favorite part of the essay is the paragraph immediately preceding the part quoted by Thomas:

"Our present system of scientific communication depends almost entirely on [literature with] three basic characteristics: it is fragmentary, derivative, and edited. These characteristics are, however, quite essential."

So, while some people may experience revelation upon reading Group Genius (like Ori Brafman), I instead find Sawyer's book to be fragmentary, derivative and edited. But those are exactly the traits that make Sawyer's book so creative and so worth reading.

BTW, check out Ziman's bibliography and see how he relies on material published in 1939.

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Social networks and organizations: Understanding the research

2007-08-21T08:48:00.000-04:00

My book report on Social Networks and Organizations, by Kilduff and Tsai. Part Two of a Series.

Chapter Two: Understanding Social Network Research. Kilduff and Tsai discuss the scientific ancestry of SNA and highlight the major distinctive concepts of the field. They state their case thus:

"At its best, network research has several distinctive features that differentiate it from traditional approaches in the social sciences:
Network research focuses on relations and the patterns of relations rather than on attributes of actors;
Network research is amenable to multiple levels of analysis, and can thus provide micro-macro linkages;
Network research can integrate quantitative, qualitative, and graphical data, allowing more thorough and in-depth analysis.
None of these features is well established in traditional approaches in the social sciences."

The authors present Exhibit A: Bruce Kapferer's analysis of strategy and transaction in an African factory. Their use of this case study is notable for a few reasons:

It was published in 1972 and so defuses the trendy stigma of ONA
Kapferer's study begins with a preface by his mentor J. Clyde Mitchell, who says, "Kapferer himself has argued cogently that social networks do not by themselves constitute a 'theory'. ... He must go beyond these data for an adequate explanation of the events he is considering." This defuses the network zealotry mention by Kilduff and Tsai in their own book's introduction, and sets up their next chapter: "Is there social network theory?"
The actual story observed by Kapferer involves the emergence of organized labor in one particular African factory. As the story opens, the workers are too decentralized to influence management. By the end, the workforce is much more centralized and successfully organizes a strike against the factory owners. I can almost hear Kilduff and Tsai snickering at the thought of management consultants trying to use this case study to sell SNA to some CEO. Everything about the story is backwards from the way we commonly preach networks and collaboration today.
The analysis by Kapferer is both strikingly thorough and strikingly ignorant of related research that is easy to see with hindsight. I guess scientists are only human after all.

At the end of this chapter, Kilduff and Tsai recommend further reading, including:

Nohria, N. and Eccles, R.G. (eds). 1992. Networks and organizations: Structure, form and action. Boston, MA: Harvard Business School Press. A broad cross-sectional collection of SNA work.

Scott, J. 2000. Social network analysis: A handbook. 2nd edn. Newbury Park, CA: Sage. The best SNA handbook available.

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Master of the universe

2007-08-15T10:50:00.000-04:00

Doing nothing has given me time to re-read Chapter 2 of Social Networks and Organizations, which I will discuss in a blog post soon. The chapter draws heavily on one particular case study, Strategy and transaction in an African factory, by Bruce Kapferer. This is no ordinary case study, but in fact a 366-page book published in 1972.

Doing nothing has given me so much time that I tracked this book down. The effort was definitely worth it--it was my first time checking out a book with my BU faculty ID. I get to keep the book for five months. I used to think three weeks with the option to renew was powerful. Now I am master of the library universe. I may not read Kapferer for four months or so, just to enjoy thinking about the poor students who are waiting to get their hands on his book.

Those of you with less than omnipotent library powers can take some solace in the knowledge that there is not one picture or map in Kapferer's entire 366 pages of exemplary network analysis. Instead, he presents the African factory network in matrix form, like so:
And, there are only two such networks presented in the whole book: one "before" and one "after." Click on the image above to see more detail and re-live 1970s typesetting.

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Doing nothing

2007-08-13T09:35:00.000-04:00

I am on a mini-hiatus, defined most notably by ignoring my email.

Reading Tao Te Ching provides lots of moral support for doing nothing. The world will survive a few days of my not fixing its problems.

Not everyone likes this philosophy. Here in Massachusetts, a new law that mandates health insurance for all residents has been widely publicized on TV with the catch-phrase: "Ignoring a problem never made one go away."

Those seeking a counter-argument to this credo should read Lewis Thomas (Dean of Yale Medical School, etc., etc.) who in Lives of a Cell wrote an essay "Your Very Good Health," which he summed up near the end by saying, "The great secret... is that most things [i.e., health problems] get better by themselves."

Digging up Thomas' classic collection of essays has given me lots of other food for thought that I can share later, when I am back to doing something.

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Memorable KM advice from Lao Tsu

2007-07-31T17:19:00.000-04:00

Inspired by Zen Motorcycles, I am reading Tao Te Ching for the first time. Paraphrasing chapters one and two, here is

Lao Tsu's guide to Knowledge Management:

ONE

The name that can be named is not the eternal name.
Without desiring names, one can see the mystery.
Ever desiring names, one can see manifestations.

TWO

Therefore the sage goes about doing nothing, teaching no-talking.
The ten thousand things rise and fall without cease,
Creating, yet not possessing,
Working, yet not taking credit.
Work is done, then forgotten.
Therefore it lasts forever.

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Fat people of the world, unite!

2007-07-30T09:44:00.000-04:00

The New England Journal of Medicine reported last week that obesity spreads through social networks. After the initial wave of headlines, I checked it out and was really impressed by the research, done by Nicholas A. Christakis and James H. Fowler.

One small (but to me significant) jewel of their research is the network movie they use to demonstrate their findings. See Judy Breck's post on SmartMobs for a link to the movie, which uses state-of-the-art network visualization algorithms to present complex data in an intuitive way. The authors used SoNIA to make the movie. (More on network movies here.)

Another gem accompanying this study is the editorial by Albert-Laszlo Barabasi. He points out the multiple levels of networks at play, which include not just social networks but also biochemical networks. Compare Barabasi's diagram to Peter Gloor's multi-level analysis of business innovation (at right) and you can see why there is actual scientific substance behind work such as Verna Allee's which "uses principles of living systems theory to help companies evolve management thinking."

Publicity like this makes it all too easy to go overboard with network science, however. Breck's otherwise solid post concludes, "A key truth the article demonstrates is that social networking is not some oddball result of the emergence of the Internet. Networking principles are deeply imbedded [sic] into the physical and psychological venues, as well as the virtual." I feel rather confident that the authors of the study would be puzzled by Breck's statement; a scan of their paper shows that they are confident enough in the foundations of network principles to use them in their work without any need to get defensive about their analysis.

What strikes me most about the study is the off-hand comment at the very end of the movie. We naturally expect obesity and non-obesity to cluster, and they do; however, as the authors note, we also see that obesity takes over the core of the social network and non-obesity moves to the periphery: Is this significant? My hunch is yes, and that there are implications for our health in this core-periphery structure.

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