Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This article studies the transmission of rumors in social networks. We consider a model with biased and unbiased agents. Biased agents want to enforce a specific decision and unbiased agents to match the true state. One agent learns the true state and sends a message to her neighbors, who decide whether or not to transmit it further. We characterize the perfect Bayesian equilibria of the game, show that the social network can act as a filter, and that biased agents may have an incentive to limit their number.