James Fowler: The Most Influential Political Scientist?

A colleague pointed me to this feature article about political scientist James Fowler. According to reporter Delle Willett, “He’s been invited to the Microsoft CEO Summit, having dinner at Bill Gates’ house with him, Warren Buffet and 100 other CEOs around the country. . . . President Obama’s campaign recently invited Fowler to help with analytics for the re-election campaign.”

I’m embarrassed to admit that my first reaction was envy: Hey, I thought I was supposed to be the big shot! But that’s not an appropriate reaction. Fowler’s a creative guy, and I expect that Bill Gates and Barack Obama will do better with his advice than without. I’m just hoping the president will get the advice of some political scientists for governing as well as campaigning.

Fowler’s work is controversial, as he has the habit of going from data to speculation. For example, from Willett’s article:

One of the things [Fowler and Christakis] found was: the people who kept their friends who became obese were actually healthier than the people who dropped their friends who became obese. “The moral of the story is, Don’t dump your friends. When you have a friend who is struggling with health problems or struggling with something negative in his or her life, the first thing you should do is try to help him deal with that problem—benefiting both of you,” advises Fowler.

Skeptical as I am, I still prefer this sort of speculation to the data-free variety. There’s a place in political science for the dry, data-hugging work of statisticians such as myself, and there’s a place for bold speculations too.

Here are my comments on some of Fowler’s recent work:

The happiness gene (also here).

Contagion of obesity (see also here).

An unrelated bit of research that made me think of Fowler and Christakis’s work on social networks, thus an example of how their work has influenced my thinking.

Altruism and voter turnout.

[Cross-posted at The Monkey Cage]

Andrew Gelman

Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University.