The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
Community detection in social networks
Abstract
The expansion of the web and emergence of a large number of social networking sites (SNS) have empowered users to easily interconnect on a shared platform. A social network can be represented by a graph consisting of a set of nodes and edges connecting these nodes. The nodes represent the individuals/entities, and the edges correspond to the interactions among them. The tendency of people with similar tastes, choices, and preferences to get associated in a social network leads to the formation of virtual clusters or communities. Detection of these communities can be beneficial for numerous applications such as finding a common research area in collaboration networks, finding a set of likeminded users for marketing and recommendations, and finding protein interaction networks in biological networks. A large number of community‐detection algorithms have been proposed and applied to several domains in the literature. This paper presents a survey of the existing algorithms and approaches for the detection of communities in social networks. We also discuss some of the applications of community detection. WIREs Data Mining Knowl Discov 2016, 6:115–135. doi: 10.1002/widm.1178 This article is categorized under: Algorithmic Development > Structure Discovery
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Citations
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Birds of a Feather: Homophily in Social Networks
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001) · Annual Review of Sociology · doi:10.1146/annurev.soc.27.1.415 · Cited by 18,567
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Indexing by latent semantic analysis
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990) · Journal of the American Society for Information Science · doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9 · Cited by 12,751
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Finding community structure in very large networks
Clauset, A., Newman, M. E. J., & Moore, C. (2004) · Physical Review E · doi:10.1103/physreve.70.066111 · Cited by 7,390
Fast algorithm for detecting community structure in networks
Newman, M. E. J. (2004) · Physical Review E · doi:10.1103/physreve.69.066133 · Cited by 5,406
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005) · Nature · doi:10.1038/nature03607 · Cited by 5,373
An Efficient Heuristic Procedure for Partitioning Graphs
Kernighan, B. W., & Lin, S. (1970) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1970.tb01770.x · Cited by 5,305
An Information Flow Model for Conflict and Fission in Small Groups
Zachary, W. W. (1977) · Journal of Anthropological Research · doi:10.1086/jar.33.4.3629752 · Cited by 4,704
Algebraic connectivity of graphs
Fiedler, M. (1973) · Czechoslovak Mathematical Journal · doi:10.21136/cmj.1973.101168 · Cited by 3,977
Near linear time algorithm to detect community structures in large-scale networks
Raghavan, U. N., Albert, R., & Kumara, S. (2007) · Physical Review E · doi:10.1103/physreve.76.036106 · Cited by 3,502
(2000) · CrossRef Listing of Deleted DOIs · doi:10.1162/jmlr.2003.3.4-5.993 · Cited by 3,024
Comparing community structure identification
Danon, L., Díaz-Guilera, A., Duch, J., & Arenas, A. (2005) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2005/09/p09008 · Cited by 2,872
Newman, M. E. J. (2004) · Physical Review E · doi:10.1103/physreve.70.056131 · Cited by 2,476
Defining and identifying communities in networks
Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., & Parisi, D. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400054101 · Cited by 2,450
Lusseau, D., Schneider, K., Boisseau, O. J., Haase, P., Slooten, E., & Dawson, S. M. (2003) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-003-0651-y · Cited by 2,277
Stochastic blockmodels and community structure in networks
Karrer, B., & Newman, M. E. J. (2011) · Physical Review E · doi:10.1103/physreve.83.016107 · Cited by 2,025
Detecting the overlapping and hierarchical community structure in complex networks
Lancichinetti, A., Fortunato, S., & Kertész, J. (2009) · New Journal of Physics · doi:10.1088/1367-2630/11/3/033015 · Cited by 1,941
Partitioning Sparse Matrices with Eigenvectors of Graphs
Pothen, A., Simon, H. D., & Liou, K.-P. (1990) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/0611030 · Cited by 1,684
Quantifying social group evolution
Palla, G., Barabási, A.-L., & Vicsek, T. (2007) · Nature · doi:10.1038/nature05670 · Cited by 1,668
Graph Clustering by Flow Simulation
van Dongen, S. M. (2000) · Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands · Cited by 1,595
Community detection in complex networks using extremal optimization
Duch, J., & Arenas, A. (2005) · Physical Review E · doi:10.1103/physreve.72.027104 · Cited by 1,549
Self-similar community structure in a network of human interactions
Guimerà, R., Danon, L., Díaz-Guilera, A., Giralt, F., & Arenas, A. (2003) · Physical Review E · doi:10.1103/physreve.68.065103 · Cited by 1,515
Finding Statistically Significant Communities in Networks
Lancichinetti, A., Radicchi, F., Ramasco, J. J., & Fortunato, S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018961 · Cited by 1,187
Cooperative Game Theory Approaches for Network Partitioning
Avrachenkov, K. E., Kondratev, A. Y., & Mazalov, V. V. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-62389-4_49 · Cited by 1,073
Lancichinetti, A., & Fortunato, S. (2009) · Physical Review E · doi:10.1103/physreve.80.016118 · Cited by 1,009
A Method of Matrix Analysis of Group Structure
Luce, R. D., & Perry, A. D. (1949) · Psychometrika · doi:10.1007/bf02289146 · Cited by 983
CFinder: locating cliques and overlapping modules in biological networks
Adamcsek, B., Palla, G., Farkas, I. J., Derényi, I., & Vicsek, T. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl039 · Cited by 933
Overlapping community detection in networks: The state-of-the-art and comparative study
Xie, J., Kelley, S., & Szymanski, B. K. (2013) · ACM Computing Surveys · doi:10.1145/2501654.2501657 · Cited by 930
Modularity from fluctuations in random graphs and complex networks
Guimerà, R., Sales-Pardo, M., & Amaral, L. A. N. (2004) · Physical Review E · doi:10.1103/physreve.70.025101 · Cited by 894
Overlapping Community Detection in Networks: the State of the Art and Comparative Study
Xie, J., Kelley, S., & Szymanski, B. K. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1110.5813 · Cited by 865
Finding overlapping communities in networks by label propagation
Gregory, S. (2010) · New Journal of Physics · doi:10.1088/1367-2630/12/10/103018 · Cited by 806
Detect overlapping and hierarchical community structure in networks
Shen, H., Cheng, X., Cai, K., & Hu, M.-B. (2009) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2008.12.021 · Cited by 723
Translation techniques in cross-language information retrieval
Zhou, D., Truran, M., Brailsford, T., Wade, V., & Ashman, H. (2012) · ACM Computing Surveys · doi:10.1145/2379776.2379777 · Cited by 698
Deep South: A Social Anthropological Study of Caste and Class
Jones, L. W., Davis, A., Gardner, B. B., & Gardner, M. R. (1942) · Southern Economic Journal · doi:10.2307/1052688 · Cited by 668
Line graphs, link partitions, and overlapping communities
Evans, T. S., & Lambiotte, R. (2009) · Physical Review E · doi:10.1103/physreve.80.016105 · Cited by 615
Tracking the Evolution of Communities in Dynamic Social Networks
Greene, D., Doyle, D., & Cunningham, P. (2010) · 2010 International Conference on Advances in Social Networks Analysis and Mining · doi:10.1109/asonam.2010.17 · Cited by 537
GA-Net: A Genetic Algorithm for Community Detection in Social Networks
Pizzuti, C. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-87700-4_107 · Cited by 481
A framework for community identification in dynamic social networks
Tantipathananandh, C., Berger-Wolf, T., & Kempe, D. (2007) · Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1281192.1281269 · Cited by 443
Detecting functional modules in the yeast protein–protein interaction network
Chen, J., & Yuan, B. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl370 · Cited by 440
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
Lin, Y.-R., Chi, Y., Zhu, S., Sundaram, H., & Tseng, B. L. (2008) · Proceedings of the 17th international conference on World Wide Web · doi:10.1145/1367497.1367590 · Cited by 407
Subnetwork hierarchies of biochemical pathways
Holme, P., Huss, M., & Jeong, H. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg033 · Cited by 367
A classification for community discovery methods in complex networks
Coscia, M., Giannotti, F., & Pedreschi, D. (2011) · Statistical Analysis and Data Mining: The ASA Data Science Journal · doi:10.1002/sam.10133 · Cited by 353
Extending the definition of modularity of directed graphs with overlapping communitiesPreprint
Nicosia, V., Mangioni, G., Carchiolo, V., & Malgeri, M. (2009) · Cited by 350
Extending the definition of modularity to directed graphs with overlapping communities
Nicosia, V, Mangioni, G., Carchiolo, V, & Malgeri, M. (2009) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2009/03/p03024 · Cited by 346
A Multiobjective Genetic Algorithm to Find Communities in Complex Networks
Pizzuti, C. (2012) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2011.2161090 · Cited by 346
E-Mail as Spectroscopy: Automated Discovery of Community Structure within Organizations
Tyler, J. R., Wilkinson, D. M., & Huberman, B. A. (2005) · The Information Society · doi:10.1080/01972240590925348 · Cited by 327
An Algorithm to Find Overlapping Community Structure in Networks
Gregory, S. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-74976-9_12 · Cited by 302
Towards Linear Time Overlapping Community Detection in Social Networks
Xie, J., & Szymanski, B. K. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-30220-6_3 · Cited by 280
Community Detection in Complex Networks Using Genetic Algorithms
Tasgin, M., Herdağdelen, A., & Bingol, H. O. (2007) · arXiv (Cornell University) · doi:10.48550/arxiv.0711.0491 · Cited by 275
Detecting highly overlapping community structure by greedy clique expansion
Lee, C., Reid, F., McDaid, A. F., & Hurley, N. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1002.1827 · Cited by 271
An Evolutionary Multiobjective Approach for Community Discovery in Dynamic Networks
Folino, F., & Pizzuti, C. (2014) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2013.131 · Cited by 265
A framework for analysis of dynamic social networks
Berger-Wolf, T. Y., & Saia, J. (2006) · Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1150402.1150462 · Cited by 253
A particle-and-density based evolutionary clustering method for dynamic networks
Kim, M.-S., & Han, J. (2009) · Proceedings of the VLDB Endowment · doi:10.14778/1687627.1687698 · Cited by 243
Community detection in large-scale social networks
Du, N., Wu, B., Pei, X., Wang, B., & Xu, L. (2007) · Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis · doi:10.1145/1348549.1348552 · Cited by 231
Fortunato, S., & Castellano, C. (2012) · Computational Complexity · doi:10.1007/978-1-4614-1800-9_33 · Cited by 215
A game-theoretic framework to identify overlapping communities in social networks
Chen, W., Liu, Z., Sun, X., & Wang, Y. (2010) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-010-0186-6 · Cited by 215
Identifying and evaluating community structure in complex networks
Steinhaeuser, K., & Chawla, N. V. (2010) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.11.001 · Cited by 203
Overlapping community detection using seed set expansion
Whang, J. J., Gleich, D. F., & Dhillon, I. S. (2013) · Proceedings of the 22nd ACM international conference on Information & Knowledge Management · doi:10.1145/2505515.2505535 · Cited by 188
Clique graphs and overlapping communities
Evans, T. S. (2010) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/2010/12/p12037 · Cited by 183
A Fast Algorithm to Find Overlapping Communities in Networks
Gregory, S. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-87479-9_45 · Cited by 174
Community analysis in social networks
Arenas, A., Danon, L., D�az-Guilera, A., Gleiser, P. M., & Guimer�, R. (2004) · The European Physical Journal B - Condensed Matter · doi:10.1140/epjb/e2004-00130-1 · Cited by 171
FINDING COMMUNITIES BY CLUSTERING A GRAPH INTO OVERLAPPING SUBGRAPHS
Baumes, J., Goldberg, M., Krishnamoorthy, M. S., Magdon‐Ismail, M., & Preston, N. (2005) · IADIS AC · Cited by 170
Survey on Social Community Detection
Plantié, M., & Crampes, M. (2013) · Computer Communications and Networks · doi:10.1007/978-1-4471-4555-4_4 · Cited by 169
Graph clustering with network structure indices
Rattigan, M. J., Maier, M. E., & Jensen, D. D. (2007) · International Conference on Machine Learning · doi:10.1145/1273496.1273595 · Cited by 165
Topic oriented community detection through social objects and link analysis in social networks
Zhao, Z., Feng, S., Wang, Q., Huang, J. Z., Williams, G. J., & Fan, J. (2011) · Knowledge-Based Systems · doi:10.1016/j.knosys.2011.07.017 · Cited by 157
On evolutionary spectral clustering
Chi, Y., Song, X., Zhou, D., Hino, K., & Tseng, B. L. (2009) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/1631162.1631165 · Cited by 147
Line graphs of weighted networks for overlapping communities
Evans, T., & Lambiotte, R. (2010) · The European Physical Journal B · doi:10.1140/epjb/e2010-00261-8 · Cited by 144
Everett, M. G., & Borgatti, S. P. (2009) · Cited by 139
LabelRank: A stabilized label propagation algorithm for community detection in networks
Xie, J., & Szymanski, B. K. (2013) · IEEE Network Science Workshop (NSW) · doi:10.1109/nsw.2013.6609210 · Cited by 138
A link clustering based overlapping community detection algorithm
Shi, C., Cai, Y., Fu, D., Dong, Y., & Wu, B. (2013) · Data & Knowledge Engineering · doi:10.1016/j.datak.2013.05.004 · Cited by 129
Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks
Wu, Z., Lin, Y., Gregory, S., Wan, H., & Tian, S. (2012) · Journal of Computer Science and Technology · doi:10.1007/s11390-012-1236-x · Cited by 128
Community detection: Topological vs. topical
Ding, Y. (2011) · Journal of Informetrics · doi:10.1016/j.joi.2011.02.006 · Cited by 123
Community detection and graph partitioning
Newman, M. E. J. (2013) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/103/28003 · Cited by 121
Xie, J., Chen, M., & Szymanski, B. K. (2013) · doi:10.1145/2489247.2489249 · Cited by 117
Dynamic Social Community Detection and Its Applications
Nguyen, N. P., Dinh, T. N., Shen, Y., & Thai, M. T. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091431 · Cited by 112
Community Evolution Mining in Dynamic Social Networks
Takaffoli, M., Sangi, F., Fagnan, J., & Zai͏̈ane, O. R. (2011) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2011.07.055 · Cited by 102
Finding Overlapping Communities Using Disjoint Community Detection Algorithms
Gregory, S. (2009) · Studies in computational intelligence · doi:10.1007/978-3-642-01206-8_5 · Cited by 97
Overlapped community detection in complex networks
Pizzuti, C. (2009) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1569901.1570019 · Cited by 78
Adaptive clustering algorithm for community detection in complex networks
Ye, Z.-Q., Hu, S., & Yu, J. M. (2008) · Physical Review E · doi:10.1103/physreve.78.046115 · Cited by 73
On efficient use of entropy centrality for social network analysis and community detection
Nikolaev, A. G., Razib, R. H., & Kucheriya, A. (2014) · Social Networks · doi:10.1016/j.socnet.2014.10.002 · Cited by 67
A fast algorithm for community detection in temporal network
He, J., & Chen, D. (2015) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2015.02.069 · Cited by 63
Fast Community Detection for Dynamic Complex Networks
Bansal, S., Bhowmick, S., & Paymal, P. (2011) · Communications in computer and information science · doi:10.1007/978-3-642-25501-4_20 · Cited by 61
Overlapping Community Discovery Methods: A Survey
Amelio, A., & Pizzuti, C. (2014) · Lecture notes in social networks · doi:10.1007/978-3-7091-1797-2_6 · Cited by 59
Effective Algorithm for Detecting Community Structure in Complex Networks Based on GA and Clustering
Liu, X., Li, D., Wang, S., & Tao, Z. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-72586-2_95 · Cited by 58
Alvari, H., Hashemi, S., & Hamzeh, A. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23887-1_79 · Cited by 56
Community detection in dynamic social networks: A game-theoretic approach
Alvari, H., Hajibagheri, A., & Sukthankar, G. (2014) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2014.6921567 · Cited by 54
Overlapping Community Detection by Collective Friendship Group Inference
Rees, B. S., & Gallagher, K. B. (2010) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2010.28 · Cited by 41
Community Detection in Dynamic Social Networks: A Game-Theoretic Approach
Alvari, H., Hajibagheri, A., & Sukthankar, G. (2015) · Cited by 37
Genetic Algorithms for community detection in social networks
Hafez, A. I., Ghali, N. I., Hassanien, A. E., & Fahmy, A. A. (2012) · International Conference on Intelligent Systems Design and Applications (ISDA) · doi:10.1109/isda.2012.6416582 · Cited by 33
A semantic overlapping community detection algorithm based on field sampling
Yu, X., Yang, J., & Xie, Z. (2014) · Expert Systems with Applications · doi:10.1016/j.eswa.2014.07.009 · Cited by 31
OCMiner: A density-based overlapping community detection method for social networks
Bhat, S. Y., & Abulais, M. (2015) · Intelligent Data Analysis · doi:10.3233/ida-150751 · Cited by 18
Genetic Algorithms Approach to Community Detection
Mazur, P., Zmarzłowski, K., & Orłowski, A. (2010) · Acta Physica Polonica A · doi:10.12693/aphyspola.117.703 · Cited by 16
Scalable community detection in massive social networks using MapReduce
Shi, J., Xue, W., Wang, W., Zhang, Y., Yang, B., & Li, J. (2013) · IBM Journal of Research and Development · doi:10.1147/jrd.2013.2251982 · Cited by 16
Semantic Topics Modeling Approach for Community Detection
Abdelbary, H., & ElKorany, A. (2013) · International Journal of Computer Applications · doi:10.5120/14020-2177 · Cited by 9
Extracting evolutionary communities in community question answering
Zhang, Z., Li, Q., Zeng, D. D., & Gao, H. (2014) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23003 · Cited by 7
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Metadata
- Authors
- Bedi, P., & Sharma, C.
- Venue
- WIREs Data Mining and Knowledge Discovery
- Publisher
- Wiley
- Published
- 2016-02-19
- Volume
- 6
- Issue
- 3
- Pages
- 115-135
- ISSN
- 1942-4787 (ISSN-L)
- 1942-4795
- OpenAlex
- W2290805605
- Cited by
- 346
- References
- 102
- FWCI
- 15.37
- Type
- journal article
- Language
- en
- Open access
- closed
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