Homophily and peer influence are messy business
Some social scientists have recently been getting themselves into trouble (and limelight) claiming that they have evidence of direct and indirect “contagion” (peer influence effects) in obesity, happiness, loneliness, etc. Statisticians and methodologists — and even science journalists — have pointed out their troubles. In observational data, peer influence effects are confounded with those of homophily and common external causes. That is, people are similar to other people in their social neighborhood because ties are more likely to form between similar people, and many external events that could cause the outcome are localized in networks (e.g., fast food restaurant opens down the street).
Econometricians1 have worked out the conditions necessary for peer influence effects to be identifiable.2 Very few studies have plausibly satisfied these requirements. But even if an investigator meets these requirements, it is worth remembering that homophily and peer influence are still tricky to think about — let along produce credible quantitative estimates of.
As Andrew Gelman notes, homophily can depend on network structure and information cascades (a kind of peer influence effect) to enable the homophilous relationships to form. Likewise, the success or failure of influence in a relationship can affect that relationship. For example, once I convert you to my way of thinking — let’s say, about climate change, we’ll be better friends. To me, it seems like some of the downstream consequences of our similarity should be attributed to peer influence. If I get fat and so you do, it could be peer influence in many ways: maybe that’s because I convinced you that owning a propane grill is more environmentally friendly (and then we both ended up grilling a lot more red meat). Sounds like peer influence to me. But it’s not that me getting fat caused you to.
Part of the problem here is looking only at peer influence effects in a single behavior or outcome at once. I look forward to the “clear thinking and adequate data” (Manski) that will allow us to better understand these processes in the future. Until then: scientists, please at least be modest in your claims and radical policy recommendations. This is messy business.
- They do statistics but speak a different language than big “S” statisticians — kind of like machine learning folks. [↩]
- For example, see Manski, C. F. (2000). Economic analysis of social interactions. Journal of Economic Perspectives, 14(3):115–136. Economists call peer influence effects endogenous interactions and contextual interactions. [↩]
I was witness to this first hand. I feel like I inspired you to run more when we lived together. I would definitely say that is an example of peer influence for sure. Second, I don’t like what you are insinuating regarding red meat and getting fat.
I think that the effects of peer influence are only going to get stronger (with regards to content) in this new sharing society (Facebook, Twitter, etc). Facebook, by default, creates a unique view into a user’s contacts, and I would argue is unbeknownst to the users (though you’d know more about that data than I). By using the default Top News view, we are letting Facebook tell us what we should care about with regards to our connections (photos, links, actions). So definitely something that I think will get more difficult to track as there are network inputs for a person now.
Yes, I think you get some credit there.
To further complicate matters: we should expect that peer behavior and peer similarity interact in complex ways. For example, if you were, e.g., female, a recent NCAA athlete, or obese — holding our relationship constant (whatever that means) — it seems like that this dissimilarity could reduce your running behavior’s influence on me. This highlights for me that once one gets into the particular messy reality of social phenomena, it is not simple as attributing some variance in the outcome to peer influence and some to homophily…
On your second point, I wonder though if what we see there is a boost to peer influence effects for weaker ties (or physically distant strong ties). In the future, I imagine that people may design their media experiences to influence themselves in desirable ways, just as some folks prefer to avoid news or dark films because it hurts their mood.