Top Persuader Prediction for Social Networks1
Authors: Fang, Xiao; Hu, Paul Jen-Hwa
Journal: MIS Quarterly (2018)
<jats:p>Top persuaders in a social network are social entities whose adoption of a product or service will result in the largest numbers of other entities in the network adopting the same product or service. Predicting top persuaders is critical to an expanding array of important social network-centric applications, such as viral marketing, customer retention, and political message promotion. This study formulates the top persuader prediction problem and develops a novel method to predict top persuaders. Our method development is rooted in eminent social network theories that reveal several forces central to social persuasion, including social influence, entity similarity, and structural equivalence. Our method innovatively integrates these forces to predict top persuaders in a social network, in contrast to existing methods that primarily focus on social influence. Specifically, we introduce persuasion probability that denotes the likelihood of persuasion conditioned on these forces. We then propose how to estimate persuasion probabilities, develop an algorithm to predict top persuaders using the estimated persuasion probabilities, and analyze the theoretical property of the algo…