Chain mail and effective flow

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:

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Competent Jerks and Lovable Fools, Part 2

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

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

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Learning and loving? at BU

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.

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Knowing the path and walking the path

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.


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10 Minutes for Marty Kearns of Netcentric Campaigns

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

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.