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.

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

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

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:


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.

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.

Please share with me so that I can beat you

[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:

1. 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
2. Direct reciprocity: you and I interact repeatedly, and I expect that over time you will repay the favors I give you now
3. 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.

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.

Economic externalities and network science

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:

1. 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.
2. 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?
3. 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.
4. 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:

1. Information externalities --> cardinality and centrality
2. Coercive externalities --> connectivity and clustering
   
3. Market externalities --> structural equivalence
   
4. 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

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.