Persuasion, News Sharing, and Cascades on Social Networks

Chin-Chia Hsu, Amir Ajorlou, Ali Jadbabaie

Abstract: We study a model of online news dissemination on a Twitter-like social network. Given a news item and its credibility, agents with heterogeneous priors strategically decide whether to share the news with their followers. An agent shares the news, if the news can persuade her followers to take an action (such as voting) in line with the agent’s perspectives. We describe the agent’s decision making and the conditions that lead to sharing the news with followers, and characterize the size of news spread at the equilibrium of the news-sharing game. We further investigate the impact of the network connectivity, heterogeneity of prior perspectives, and news credibility on the set of the news that can trigger a sharing cascade. Finally, we identify the conditions under which the news with low credibility can spread wider than highly credible news. In particular, we show that when the network is highly-connected or the news is not a "tail event", a sharing cascade can occur even with news that is not credible.