Comparing Group Characteristics to Explain Community Structures in Social Media Networks

Abstract

Recently, the identification of community structures among social media networks (SMNs) becomes a hot topic. The characteristics of SMNs have typically been analyzed by clustering SMN users based on their relationships. However, popular SMNs such as LiveJournal and Flickr allow users to join or create communities according to their personal interests. In contrast to previous studies that have typically employed cluster strategies to categorize SMN users, this paper examines the communities that users have joined, i.e., people can belong to multiple communities. The structures are analyzed using data collected from four popular SMNs, namely, LiveJournal, Flickr, Orkut, and YouTube. Several measurements are proposed to model the characteristics and structures of these communities, and the experimental results show that the interconnection among communities is high, especially among Flickr and YouTube users. The findings of this study differ considerably from previous studies that have applied a cluster analysis methodology.