Assessing scale-free scaling and robustness in an online community network

Abstract

While extensive studies on various networks properties have been carried out, little has been done on large-scale online community networks. An online community network essentially is a group-centered online platform, that is much different from traditional social network. Based on the log data of a university online community, we investigate the statistical characteristics of the evolving network during the different observation period, and find that the degree distribution of the network follows a composite power laws form. In addition, the online community network shows the small world effect, well-interconnected modules, and the hallmark of “scale-free”. Further research indicates that the online community network is high robust to random removals, but fail to intentional attacks, especially to attacks based on the betweenness, that shows some nodes with high betweenness play a key role in maintaining the online community network communication capabilities. Our analysis aims to provide a platform for drawing a host of practical implications for information diffusion and promoting valuable communication, as well as for the management and design of online communities.