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doi: 10.1111/iere.12275
AbstractThis 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.
Bayesian updating,Rumors,Misinformation,Social networks, 330, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SHS.ECO] Humanities and Social Sciences/Economics and Finance
Bayesian updating,Rumors,Misinformation,Social networks, 330, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SHS.ECO] Humanities and Social Sciences/Economics and Finance
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 42 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |