2008/11/25 by Benjamin Golub, Matthew O. Jackson, Golub, Benjamin +1
Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Statistics and Probability (physics.data-an) #physics.data-an #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.0811.4013
Expanded version includes additional empirical analysis
arxiv created 2009/02/09 · arxiv updated 2009/12/01
We examine how three different communication processes operating through social networks are affected by homophily -- the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are broadcast or sent via shortest paths; only connection density matters. In contrast, homophily substantially slows learning based on repeated averaging of neighbors' information and Markovian diffusion processes such as the Google random surfer model. Indeed, the latter processes are strongly affected by homophily but completely independent of connection density, provided this density exceeds a low threshold. We obtain these results by establishing new results on the spectra of large random graphs and relating the spectra to homophily. We conclude by checking the theoretical predictions using observed high school friendship networks from the Adolescent Health dataset.