Multiplexing in networks and diffusion - Arun G. Chandrasekhar; Vasu Chaudhary; Benjamin Golub; Matthew O. Jackson (Proceedings of the National Academy of Sciences, 2026)
We study multiplexing—the extent to which people have multiple, distinct types of relationships with the same others. 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. On the theoretical side, 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 spread through a single interaction. 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. Finally, we identify empirical differences in multiplexing by gender and connectedness.