A review on community structures detection in time evolving social networks
Norah Alotaibi, Delel Rhouma
Abstract
The usage of social networks has widely increased in recent years. Humans tend to form groups, in these networks, based on their similar interests. Such groups are known as communities or clusters. Detecting such structure gives us an exceptional understanding of the organization and function of social networks. This problem is amplified because networks evolve, so their structure changes. This survey highlights the characteristics and challenges of the community detection problem in dynamic social networks, motivated by this evolution. Our paper investigated and compared state-of-the-art methods technically. This survey will help researchers find the best methods and choose the relevant future direction because of the definition of network models and problem formation.