Probabilistic Snapshot Based Evolutionary Social Network Events Detection

Most of the existing researches simply convert associations of nodes within the snapshot of the evolutionary social network to the weight of edges. However, because of the obvious Matthew effect existing in the interactions of nodes in the real social network, the association strength matrices extracted directly by snapshots are extremely uneven. This paper introduces a new evolutionary social network model. Firstly, we generate probabilistic snapshots of the evolutionary social network data. Afterwards, we use the probabilistic factor model to detect the variation points brought by network events. According to experimental results, our proposed probabilistic snapshot model of evolutionary social network is effective for network events detection.