Peer Effects and Peer Avoidance: The Diffusion of Behavior in Coevolving Networks
研究了动态复杂网络中个体行为（好行为G与坏行为B）的长期涌现模式，发现网络与行为共同演化时，同伴回避机制能显著支持好行为的维持，为理解同伴压力对行为扩散的作用提供了新视角。
We study the long-run emergence of behavioral patterns in dynamic complex networks. Individuals can display two kinds of behavior: G (“good”) or B (“bad”). We assume that the exposure of a G agent to bad behavior on the part of peers/neighbors triggers her own switch to B behavior, but only temporarily. We model the implications of such peer effects as an epidemic process in the standard SIS (Susceptible-Infected-Susceptible) framework. The key novelty of our model is that, unlike in the received literature, the network is taken to change over time within the same time scale as behavior. Specifically, we posit that links connecting two G agents last longer, reflecting the idea that B agents tend to be avoided. The main concern of the paper is to understand the extent to which such biased network turnover may play a significant role in supporting G behavior in a social system. And indeed we find that network coevolution has nontrivial and interesting effects on long-run behavior. This yields fresh insights on the role of (endogenous) peer pressure on the diffusion of social behavior and also has some bearing on the traditional study of disease epidemics.