Mahsa Nooribakhsh - Department of Business Organization, Universitat Politècnica de València, Camino de Vera, s/n, ۴۶۰۲۲ Valencia,Spain
Fernando González-Ladrón-De-Guevara - epartment of Business Organization, Universitat Politècnica de València, Camino de Vera, s/n, ۴۶۰۲۲ Valencia,Spain
Marta Fernández-Diego - epartment of Business Organization, Universitat Politècnica de València, Camino de Vera, s/n, ۴۶۰۲۲ Valencia,Spain
Mahdi Mollamotalebi - Department of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin,Iran

Nowadays, analysis of social networks has emerged as one of the research issues related to artificial intelligence-basedalgorithms. The development of social networks in recent years has led to interest the people using them. The members of socialnetworks use them to create different online groups and make an easy and continuous relation. All aspects of life are influencedby social networks so that user behavior analysis particularly community/cluster discovery has become one of the recentresearch topics. Communities in social networks are groups of people whose relationships are much greater than those of otherpeople. Investigating the social network communities leads to get more information about the behavior of their members todifferent goals such as sale prediction, security, scientific aspects, etc. With regard to the importance of discovering socialnetworks communities, this paper presents a brief review of artificial intelligence-based algorithms to this matter. The resultsof the research indicates that machine learning-based algorithms are the most prevalent in this regard.

Social networks, Community detection, Artificial intelligence, Machine learning