research

There is increasing evidence that social media is detrimental to mental health and self-esteem. A puzzle is why, in spite of this, people join these platforms. One possibility is that people feel compelled to participate: they dislike these networks—in particular, the way in which they generate rat races—but they need to be on them to socialize with peers. We refer to networks that harm users as “bad networks”. We model settings with network externalities and show that, surprisingly, bad networks are easy to establish. We also show that networks tend to be both bad and easy to establish when they create rat races—as social networks often do. Amplifying the rat race boosts network size which, while harmful to consumers, may benefit the platform.

A growing body of empirical evidence reveals a fundamental asymmetry in the diffusion of social behaviors: prosocial behaviors often exhibit strategic substitutability (“bystander effects”), while antisocial behaviors exhibit strategic complementarities (“licensing effects”). Moreover, even a single behavior (e.g., protest participation) can be a complement in some settings and a substitute in others. To unify these findings, we develop a model of strategic diffusion on networks with positive (prosocial) or negative (antisocial) spillovers. Our results rely on a novel conception of influence, capturing the causal impact of an individual’s adoption on others. Prosocial behaviors are complementary in sparse networks but substitutable in dense ones, while antisocial behaviors exhibit the reverse pattern. Our model predicts that prosocial behaviors emerge continuously, while antisocial behaviors exhibit a discontinuous, sudden emergence. Effective policies can target the network density or perceptions of the extent of spillovers to encourage prosocial behaviors and inhibit antisocial ones.

Sender maximizes how many receivers buy a widget of uncertain quality. She targets receivers to privately communicate information about the widget’s quality. After the target chooses whether to buy the widget, other receivers observe the target’s choice with probability increasing in the target’s popularity. We prove two results that hold remarkably generally: Sender optimally communicates with targets as if no other receiver exists; a target’s popularity is a double-edged sword for Sender. We fully characterize the optimal choice of a single target under multiple communication protocols and establish that Sender can benefit from protocols that constrain her communication.

Many social and economic behaviors, from participating in a protest to adopting a new technology, require reinforcement from multiple peers to be worthwhile. The spread of these behaviors is often called complex contagion. We develop a tractable model of complex contagion on random networks, where agents take an action only when enough peers do too. We identify a tipping point in behavior: a level of network connectivity where participation (the fraction taking the action) jumps discontinuously. We characterize how the location and size of this tipping point depend on heterogeneity in connectivity among agents. When a principal with coarse control over the network structure likes connectivity but dislikes participation, she is pushed into “extreme” choices. She either chooses no participation, or a level significantly above the tipping point: to accept any participation is to accept a lot. The principal is “in for a penny, in for a pound”.