Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

TL;DR

This paper demonstrates that in observational social network studies, homophily, contagion, and covariate effects are generally confounded, making causal inference challenging without strong assumptions or adequate covariates.

Contribution

It reveals the inherent confounding among homophily, contagion, and covariate effects in social networks and discusses the limitations of simple models in identifying causal relationships.

Findings

Regression asymmetries cannot identify causal effects.

Simple imitation models can produce correlations without intrinsic affinity.

Confounding is generic without strong assumptions or covariates.

Abstract

We consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual's covariates on their behavior or other measurable responses. We show that, generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular we demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects, and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual's enduring traits and their choices, even when there is no intrinsic affinity between them. We also suggest some possible constructive responses to these results.