Multiplexing in networks and diffusion

Social and economic networks are often multiplexed, meaning that people are connected by different types of relationships---such as borrowing goods and giving advice. We make two contributions to the study of multiplexing and the understanding of simple versus complex contagion. On the theoretical side, we introduce a model and theoretical results about diffusion in multiplex networks. We show that increased overlap in people's different types of relationships impedes the spread of simple contagions, such as diseases or basic information that only require one interaction to transmit an infection. In contrast, such higher levels of multiplexing enhance the spread of a complex contagion (e.g., a behavior or belief that requires multiple interactions for transmission) when infection rates are low, but impede complex contagion if infection rates are high. On the empirical side, we document empirical multiplexing patterns in Indian village data. We show that relationships such as socializing, advising, helping, and lending are correlated but distinct, while commonly used proxies for networks based on ethnicity and geography are nearly uncorrelated with actual relationships. We also show that these layers and their overlap affect information diffusion in a field experiment. The advice network is the best predictor of diffusion, but combining layers improves predictions further. Villages with greater overlap between layers---more multiplexing---experience less overall diffusion. Finally, we identify differences in multiplexing by gender and connectedness. The theoretical and empirical results have significant implications for inequality in diffusion-mediated outcomes such as access to information and adherence to norms.