Social network is one of the most important complex networks, which aims to describe the interactive relationship among a group of active actors that represent different kind of structure. Many systems in the real world such as human societies and different types of components can be modeled as social networks. We can represent such a network in terms of graphical community. Social Network Analysis provides inherent research due to success of social media sites and social content sharing facility. Social Network Analysis provides key terms to provide platform for industry to generate survey of product and facilitate to introduce new innovation ideas to public entity. Now a day, as increase the use of social media sites provide the entrepreneurs and user to define new concept of community creation that represents the relationship of users that might be interested in same kind of activity. To create such communities introduce new research area for researcher. This community detection is different from traditional clustering. In This paper, we propose new algorithm for community detection in social network to get some meaningful and important information.

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The analysis of complex networks like social, biological network is a new era of research in information mining. The analysis of social networks has gained considerable attention in the current era, mainly due to the high growth of social networks and content exchange sites. A social network can be seen as a complex interconnection of social entities in terms of vertex and nodes. The detection of the community is the task of grouping social entities based on the linking of nodes and relationships. Most of the research has been done on the basis of grouping algorithms and extraction techniques. There are many problems associated with the task of researching social group and network analysis, such as the grouping of nodes, community mining, the generation of graphics, the prediction of links. The detection of the community in the mining of social networks is different from the traditional grouping methods. Community detection is a way to recognize the network nodes in a group or community within which the property of identified vertices is maximized in terms of similarity. Communities can have concrete applications.