Yesterday’s post on Using Metadata to Find Paul Revere really caught fire. It’s still going, in fact, and it will probably break a hundred thousand unique pageviews some time this afternoon. It’s always exciting and a little anxiety-making when something like that happens. Overall, I’m delighted that the response has been so positive. By way of follow-up, I’d just say that it’s a single post that was meant to make a point in an accessible and hopefully entertaining way. It’s not a serious piece of history, or a serious piece of social network analysis. The goal was to give people who don’t know anything about network analysis some kind of flavor or how it works and why it is powerful.
One or two people weren’t sure whether the membership information was “really” metadata. But the term is being used in current political debate to distinguish between recording the actual content of a conversation or meeting and “merely” recording that a conversation or meeting took place. So in that sense, a record of membership is “metadata” to the content of any particular meeting.
A historian mentioned to me that more recent work in her field has questioned whether the table published in Fischer’s book is completely accurate. That was new to me. It would be easy, I think, to flesh out the end of the original piece to include the case where the data is incomplete or wrong.
A few people emailed to say that contemporary SNA methods differ in significant respects or, more substantively, that network theorists have moved away from the strong picture of pure structure that they advocated in the early days. In response I can only say, again, that the the purpose of the post was not to do a contemporary piece of SNA on Fischer’s data. As I learned yesterday from Michael Chwe, Shin-Kap Han has already done this. I wanted to give non-specialists a sense of how the structural analysis of what’s being called “metadata” works, and to show in a fun but hopefully telling way how much you can get out of that approach. So I tried to emphasize that I was using one of the earliest, and (in retrospect) most basic methods we have, but one that still has the capacity to surprise people unfamiliar with SNA. Even though I am not a network specialist, I do know about the content and limits of the approach I talked about, I understand how it developed, and I know the more recent work in that tradition, too. I was lucky enough to be Ron Breiger’s colleague at Arizona for seven years, after all, and here at Duke I get to hang out around DNAC with colleagues like Jim Moody, Nan Lin, Martin Ruef, and many others working on networks.