Illusion of diffusion: A percolation perspective on social structure and segregation in Twitter networks

Abstract

Some diffusion trajectories produce cohesion while others generate highly fragmented social networks. Nevertheless, extant diffusion-based theoretical frameworks often assume continuous, gradual patterns of information flow and cascades and therefore cannot explain such disparity. Drawing on the percolation theory, which asserts that information propagation occurs abruptly and radically, this study conducts an empirical investigation into such structural integration or percolation efficiency in online social networks. In addition, we examine the roles of different characteristics of nodes and links, thereby identifying the detailed mechanism. The results demonstrate that node and link types significantly influence percolation efficiency. Regarding node types, influentials and broadcasters contribute to enhancing percolation efficiency, with the latter exhibiting a more substantial impact than the former. Hidden influentials exhibit a negligible effect on percolation efficiency, while common users negatively impact the efficiency of percolation. With respect to link types, incoming, outgoing, and bridge links serve to augment percolation efficiency. Overlap and adding links do not influence the efficiency of percolation, whereas new channel links impedes effective percolation. Based on a new theoretical perspective, this study extends research on information diffusion and word-of-mouth and provides stylized insights into effective social media targeting and advertising.