Cascading Behavior and Information Diffusion in Overlapping Clusters

Woojung Lee, Joyce Jiyoung Whang

http://doi.org/10.5626/JOK.2020.47.4.422

Information diffusion models formulate and explain cascading behavior in networks where a small set of initial adopters is assumed to acquire new information and the new information is propagated to the other nodes in the network. Most existing information diffusion models assume that a node in a network belongs to only one cluster, and based on this assumption, it has been shown that clusters are obstacles to cascades. However, in many real-world networks, a node can belong to multiple clusters, i.e., clusters can overlap. In this paper, we study cascading behavior in a network when clusters overlap. We show that clusters are not obstacles to cascades if the initial adopters are placed in the overlapped region between the clusters or if we allow compatibility. We verify our theorems and models on four real-world datasets.