Community structure is an important feature of complex networks and social network communities refer to groups of individuals within which social interactions are intense and between which they are weak. Community detection algorithms answer a wide range of questions regarding the behavior and interaction patterns of people. Usually, communities in social network can overlap with each other. Detecting overlapping communities is very important to understand and analyze the structure of social network. Approaches to find overlapping nodes in complex networks are categorized based on group density, dynamic agents, fuzzy logic and local expansion and optimization. This paper reviews the characteristics and limitations of clique percolation techniques, fuzzy approach, label propagation algorithms and local expansion and optimization techniques.
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