Is Facebook “Naturally Occurring”?
| Gabriel |
Lewis, Gonzalez, and Kaufman have a forthcoming paper in PNAS on “Social selection and peer influence in an online social network.” The project uses Facebook data from the entire college experience of a single cohort of undergrads at one school in order to pick at the perennial homophily/influence question. (Also see earlier papers from this project).
Overall it’s an excellent study. The data collection and modeling efforts are extremely impressive. Moreover I’m very sympathetic to (and plan to regularly cite) the conclusion that contagious diffusion is over-rated and we need to consider the micro-motives and mechanisms underlying contagion. I especially liked how they synthesize the Bourdieu tradition with diffusion to argue that diffusion is most likely for taste markers that are distinctive in both sense of the term. As is often the case with PNAS or Science, the really good stuff is in the appendix and in this case it gets downright comical as they apply some very heavy analytical firepower to trying to understand why hipsters are such pretentious assholes before giving up and delegating the issue to ethnography.
The thing that really got me thinking though was a claim they make in the methods section:
Because data on Facebook are naturally occurring, we avoided interviewer effects, recall limitations, and other sources of measurement error endemic to survey-based network research
That is, the authors are reifying Facebook as “natural.” If all they mean is that they’re taking a fly on the wall observational approach, without even the intervention of survey interviews, then yes, this is naturally occurring data. However I don’t think that observational necessarily means natural. If researchers themselves imposed reciprocity, used a triadic closure algorithm to prime recall, and discouraged the deletion of old ties; we’d recognize this as a measurement issue. It’s debatable whether it’s any more natural if Mark Zuckerberg is the one making these operational measurement decisions instead of Kevin Lewis.
Another way to put this is to ask where does social reality end and observation of it begin? In asking the question I’m not saying that there’s a clean answer. On one end of the spectrum we might have your basic random-digit dialing opinion survey that asks people to answer ambiguously-worded Likert-scale questions about issues they don’t otherwise think about. On the other end of the spectrum we might have well-executed ethnography. Sure, scraping Facebook isn’t as unnatural as the survey but neither is it as natural as the ethnography. Of course, as the information regimes literature suggests to us, you can’t really say that polls aren’t natural either insofar as their unnatural results leak out of the ivory tower and become a part of society themselves. (This is most obviously true for things like the unemployment rate and presidential approval ratings).
At a certain point something goes from figure to ground and it becomes practical, and perhaps even ontologically valid, to treat it as natural. You can make a very good argument that market exchange is a social construction that was either entirely unknown or only marginally important for most of human history. However at the present the market so thoroughly structures and saturates our lives that it’s practical to more or less take it for granted when understanding modern societies and only invoke the market’s contingent nature as a scope condition to avoid excessive generalization of economics beyond modern life and into the past, across cultures, and the deep grammar of human nature.
We are, God help us, rapidly approaching a situation where online social networks structure and constitute interaction. Once we do, the biases built into these systems are no longer measurement issues but will be constitutive of social structure. During the transitional period we find ourselves in though, let’s recognize that these networks are human artifices that are in the process of being incorporated into social life. We need a middle ground between “worthless” and “natural” for understanding social media data.