The mesocopic structural analysis of communities within facebook higher education online groups

To understand the social dynamics of the online generation, for example interactions, sharing and their social ties are a crucial and challenging task in the field of computer science. Mainly, due to the unprecedented growth of Online Social Media Networks (OSMNs). In this paper, we talk about community identification and its analysis of aggregation patterns and social dynamics which occurs among the members of the most popular social networking site, Facebook.. The life cycle to detect and analyse the online communities formed in these networks, begins with the acquiring of data sets from Facebook Higher Education (HE) social networks, which has been studied only on synthetic networks but not on real-world networks. We discuss in detail various mesoscopic features of community structure of these HE networks for this only we acquired the real-world HE networks by using different network analysis software applications (NASA). These networks contain hundreds of users and their social relationships; after that we discovered the communities represents the clusters or aggregated units among the members of the networks. Lastly, we analysed the communities statistical properties, finding and characterizing some specific motifs, followed by HE network's members. This research paper provides some clues of the user's tendency to gain social interactions in OSMNs that eventually helps in constructing a well-organised and connected social structure and further opens space for the social network analysis.