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Communities discovered from social networks facilitate its members so as to interact with relatable people who have similar or comparable interests. However, in present time, the enormous growth of social networks demands an intensive investigation of recent work carried out for identifying community division in social networks. This paper is an attempt to enlighten the ongoing developments in the domain of Community detection (CD) for SNA. Additionally, it sheds light on the algorithms which use meta-heuristic optimisation techniques to hit upon the community structure in social networks. Further, this paper gives a comparison of proposed methods in recent years and most frequently used optimisation approaches in the domain of CD.\u00a0It also describes some application areas where CD methods have been used. This guides and encourages researchers to probe and take ahead the work in the area of detecting communities from social networks. <\/jats:p>","DOI":"10.1142\/s0219649219500199","type":"journal-article","created":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T03:09:26Z","timestamp":1559099366000},"page":"1950019","source":"Crossref","is-referenced-by-count":6,"title":["Community Detection in Social Networks: Literature Review"],"prefix":"10.1142","volume":"18","author":[{"given":"Seema","family":"Rani","sequence":"first","affiliation":[{"name":"Department of Computer Science, Jamia Millia Islamia, New Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monica","family":"Mehrotra","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jamia Millia Islamia, New Delhi, 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