Homophily in Online Social Networks

We develop a parsimonious and tractable dynamic social network formation model in which agents interact in overlapping social groups. The model allows us to analyse network properties and homophily patterns simultaneously. We derive analytical expressions for the distributions of degree and, importantly, of homophily indices, using mean-field approximations. We test our model using a large dataset from Facebook covering student friendship networks in 10 American colleges in 2005. We find that our analytical expressions and simulations fit the homophily patterns, degree distribution, and individual clustering coefficients well with the data.