A Dynamic Information Dissemination Model Based on Implicit Link and Social Influence

Abstract

In the field of social information dissemination, current studies are mainly based on the network topology with an explicit user link. Implicit link in this study indicates users who often participate in the same topic due to certain interests or game relationships, but no explicit “following-followed” link exists among these users. In this article, the implicit link is regarded as one of the driving factors of users to participate in information dissemination, and then the network topology with the implicit link is established. First, we excavate implicit relationships among users to strengthen friends' influence in driving information dissemination and then establish a more accurate network topology. Second, we extract the individual and friend driving mechanisms based on the accurate network topology, analyze the causes of two information dynamics, and measure social influence based on a multiple linear regression model. Finally, considering the timeliness and uncertainty of information dissemination in an infectious disease model, we introduce the mean-field theory and obtain an information dissemination model based on social influence. The experimental results show that the implicit link plays an important role in driving user behavior, and the model can well explain the process of information transmission and explore the dynamic factors of information dissemination.