Identification of Communities from Social Networks

A social network is a social structure of people, related (directly or indirectly) to each other through a common relation or interest. Social network analysis (SNA) is the study of social networks to understand their structure and behavior. For studying structural and behavioral properties of these networks, communities are identified by grouping of individuals according to given context into subgroups. Community detection is very rich domain in social network analysis as it is useful in various domains like business, marketing, healthcare etc. Data analytic techniques such as data mining and predictive modeling are being used to gain new insights into social network analysis (SNA). This has the unique ability to play a new role in exploring the context and situations that lead to efficient and effective predictions. Identifying these social communities can bring benefit to understanding and predicting user’s behaviors. This paper is an attempt to study the various approaches for community detection (CD), application area of CD and evaluation of CD algorithm. It also presents the emerging and ongoing research towards improvement in existing CD algorithms in the area of social network analysis.