Web science, Webwhompers

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 Facebook and Touchgraph

Network Structure

Hubs, clusters, and other basic structural features of the Web: Network Structure Connected: a word of many meanings Induced Subgraphs "Connected" defined formally Connected graphs and connected components Hubs Clusters Defining clusters, part one: connected components Defining clusters, part two: cliques Defining clusters, part three 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. All the above are summarized in the following table: Random graphs Clustering Centrality Real-world phenomenon explained by model Giant component forms quickly when |E| ≅ |V|. Clusters emerge, providing "table of contents" overview. Hubs emerge, indicating popularity and/or influence. Web sites N/A Clusty, iBoogie, Grokker Google et al Sociological force Chance Homophily Cumulative advantage Mathematical model Random graph algorithm Triadic closure algorithm Preferential attachment algorithm

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

See also

• Six Degrees Chapter 7 pp 202-204: Diners' Dilemma and Tragedy of the Commons
• Prisoners' Dilemma by Serendip; also "What's so important about this game"
• Six Degrees Chapter 7 pp 215-219: Coordination Externalities
• Tragedy of the Anti-Commons (aka "The Permission Problem") by James Surowiecki, The New Yorker, August 2008

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.

Notable roles in living systems

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

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

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

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:

1. Introduction To Politics And Civic Leadership
2. Philosophy And Theories Of Political And Civic Leadership
3. Purposes Of Political And Civic Leadership
4. The Failure Of Politics
5. The Processes Of Political And Civic Leadership
6. The Institutions Of Political And Civic Leadership
7. The Contexts Of Public Leadership
8. The Psychology Of Public Leadership
9. The Tasks And Tools Of Political And Civic Leadership
10. The Competencies Of Public Leadership
11. 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?

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

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."

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.

Following the world's greatest RSS feed

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.
  

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.

Twitter: timing is everything...?

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

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

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

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:

• Leadership Development
• Performance & Innovation
• Community & Social Change
• Group Incentives
• Evaluation
• Social Capital
• Social Networks
• Network Building
• Network Analysis
• Software and Visualization

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.

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.

Leadership for a New Era

"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

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:

Peer leadership Organizational leadership

Field-policy leadership Collective leadership

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.

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.

Student leadership: thank you Sidney Efromovich

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

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

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

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.