Title :
A survey on community detection methods based on the nature of social networks
Author :
Pourkazemi, Maryam ; Keyvanpour, Mohammadreza
Author_Institution :
Dept. of Electron., Comput. & IT, Islamic Azad Univ., Qazvin, Iran
fDate :
Oct. 31 2013-Nov. 1 2013
Abstract :
Social networks are defined as a set of actors and relationships that represent the interactions between entities in the network. Since social networks have important roles in the dissemination of information and innovation, the analysis of such networks, attracted much attention in the research area. One of the important features of social networks is community structure. So far, several methods have been proposed to detect communities, which represent the high importance of discovering communities for understanding social networks and detecting the useful and hidden patterns in the aforementioned network. However, due to extended issue of social networks and also existing the large numbers of approaches, accurate assessment of such methods are being difficult. Therefore, for survey each proposed approach in this paper, besides introducing various types of social network, suggests a classification for community detection methods based on type and nature of social networks. Using the classification presented in this paper can play an effective role in the analysis and evaluation of community detection approaches in different application domains.
Keywords :
graph theory; social networking (online); community detection methods; information dissemination; social networks; Communities; Data mining; Heuristic algorithms; Lead; community; community detection; community evolution; modularity; social network;
Conference_Titel :
Computer and Knowledge Engineering (ICCKE), 2013 3th International eConference on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4799-2092-1
DOI :
10.1109/ICCKE.2013.6682855