Effects of Truss Structure of Social Network on Information Diffusion Among Twitter Users

Abstract

Analyzing the factors that affect information diffusion through social media is an important research topic for several applications such as realizing effective viral marketing campaigns and preventing the spread of fake news. In this paper, we focus on the community structure of a social network of social media users as a factor affecting information diffusion among those users. We extract two types of community structures, a flow truss and a cycle truss, from the social network of Twitter users and analyze how these structures affect diffusion via cascades of retweets on Twitter. Our results show that tweets disseminated via inter-community retweets have future popularity about 1.2-fold that of tweets disseminated via intra-community retweets. Our results also show that tweets disseminated within a strongly clustered community tend to have less diffusion than tweets disseminated within a weakly clustered community. These results are found both when extracting via cycle truss and flow truss communities, which suggests that our findings are robust against the definitions of community.