A multi-theoretical framework for hypotheses testing of temporal network patterns

Online social networks are multi-dimensional and dynamic. By combining these two perspectives, we can differentiate between various temporal patterns, better understand the mechanisms behind network formation, and test theories that are potentially associated with the behaviors of individuals online. In this study, we develop a temporal network analysis model and a multi-theoretical framework for examining various temporal network patterns in multi-dimensional networks. The proposed framework suggests a list of temporal patterns that may be observed in online social networks, including temporal reciprocity, co-occurrence, triangle, and k-star. We also provide theoretical explanations for why these patterns could be observed. This study provides a generalized framework to explore, analyze, and explain various temporal patterns in online social networks. An empirical test of our framework in the context of online social communities is outlined. The extended multi-theoretical framework can be easily applied to any social network that shows multi-dimensionality.