The International Journal Of Engineering And Science (IJES)
Recent years have seen an explosive growth of various online communities. The processes by which communities come together, attract new members and develop over time is a central research issue in the social sciences-political movements, professional organizations and religious denominations all provide fundamental examples of such communities. In the digital domain, on-line groups are becoming increasingly prominent due to the growth of community and social networking sites such as MySpace, Twitter. However, the challenge of collecting and analyzing large-scale time resolved data on social groups and communities has left most basic questions about the evolution of such groups largely unresolved: what are the structural features that influence whether individuals will join communities, which communities will grow rapidly and how do the overlaps among pairs of communities change over time? So considering these, in this paper, the authors present a framework for modeling and detecting community evolution in social networks.