Spiral of Silence in Social Networks: A Data-driven Approach

Although the spiral of silence theory has been studied thoroughly in the traditional dissemination field, to our best knowledge, no one has clearly verified the applicability of the spiral of silence theory in social networks based on the real information propagation datasets. In this paper, we focus on the disparity between majority and minority opinions, we verify the applicability of the spiral of silence theory in social networks by taking into account 4 factors, including the propagation width, the propagation depth, the message sentiment and the modularity through a large amount of data-driven experiments based on the real-world information propagation datasets which collected on Sina Weibo. We also investigate the applicability of tweets with different categories, our data-driven experimental results show that the spiral of silence theory is still applicable in social networks but different tweets with different categories have different applicability of the spiral of silence theory.