Multiplexing in Networks and Diffusion

TL;DR

This paper studies how multiplexed social networks influence the spread of contagions, showing that multiplexing can both hinder simple contagions and enhance complex ones, with empirical evidence from Indian villages.

Contribution

It introduces a theoretical model of diffusion in multiplex networks and provides empirical analysis of multiplexing patterns and their effects on information spread.

Findings

Multiplexing impedes simple contagion spread.

Multiplexing enhances complex contagion at low infection rates.

Greater multiplexing overlap reduces overall diffusion.

Abstract

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 multiplexing impedes the spread of simple contagions, such as diseases or basic information that only require one interaction to transmit an infection. We show, however that multiplexing enhances the spread of a complex contagion when infection rates are low, but then impedes complex contagion if infection rates become 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. These have implications for inequality in diffusion-mediated outcomes such as access to information and adherence to norms.