LAUSR

Abstract Over recent years, the usage of social networks has widely increased. In these networks, humans tend to form groups based o their similar interests. Such groups are known as communities or clusters. Detecting such structure gives us an exceptional understanding of the organizations and functions of the social networks. This problem is amplified by the fact that networks evolve over time, so their structure change. Motivated by this fact, the goal of this survey is to highlight the characteristics and challenges of the community detection problem in dynamic social networks. Our paper investigated and compared the state-of-the-art methods in a technical way. Due to the definition of network models and problem formulation, this review will help researchers to find the best methods and choose the relevant future direction.