Influential node detection in social network during community detection

The proliferation of social media has inundated a gamut of research purviews e.g. Node classification, Community analysis, Behavioral psychological in social media. Out of these research issues the study of role of individual in terms of influential phrase plays a crucial role in deciding the future and popularity of any online social community. With the deep analysis of the community, the various parameters like: density, clustering coefficient, degree centrality, closeness centrality, eigenvector centrality etc. can be extracted with an effective and reliable way. These features can be easily exploited to determine the most influential individual /node in an online community. Motivated by the complexity of research problem of finding most influential nodes in an online evolving community, this paper is an effort to understand and model the complexity of the dynamics of different metrics of social network. The proposed scheme is corroborated with the rigorous result analysis.