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.