Organizational and network leadership

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).
  

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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

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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.

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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.