Benjamin Golub — Page 2

arXiv2010

Strategic Random Networks: Why Social Networking Technology Matters

This paper develops strategic foundations for an important statistical model of random networks with heterogeneous expected degrees. Based on this, we show how social networking services that subtly alter the costs and indirect benefits of relationships can cause large changes in behavior and welfare. In the model, agents who value friends and friends of friends choose how much to socialize, which increases the probabilities of links but is costly. There is a sharp transition from fragmented, sparse equilibrium networks to connected, dense ones when the value of friends of friends crosses a cost-dependent threshold. This transition mitigates an extreme inefficiency.

stat.AP↗

arXiv2009

How Homophily Affects Diffusion and Learning in Networks

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.

physics.soc-ph↗