Abstract

Models of content-sharing behavior on online social media platforms typically represent content spread as a diffusion process modeled on contagious diseases; users’ behavior is modeled with single-agent decision theory. However, social media platforms are interactive spaces where users care about reactions to, and further spread of, the content they post. Thus, social media interaction falls under the intended use cases for game theory. In contrast to existing models leaving strategic reasoning out, we capture agents’ social media decisions within a cognitive hierarchy framework, which can be interpreted as making formally precise how agents make strategic choices based on mutual expectations of rationality. Analytically, we identify limit cases in which a platform can be swamped with content that no agents personally like but all expect to elicit reactions (think obvious fake-news). We then use agent-based simulations to show that a range of more realistic cases give rise to similar outcomes.