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Abstract
There are many real networks that are closely formed according to a community network. Many researchers have devoted their research efforts to develop algorithms and methods that can efficiently find the hidden pattern in the network which is called community. As there are different kinds of networks having different level of complexity and each may contain different properties, each algorithm in literature holds some of these properties and has different definition of community. As per the definitions provided and algorithms used, only part of the features of real communities gets extracted. Objective of this paper is to find different community detection techniques that are already available, analyze them and find the problem in these algorithms. Objective of paper is to categorize the different community discovery methods on the basis of properties these algorithms contain. The classification is also helpful in further research in community detection.