References
- Aggarwal, C and Subbian, K. 2014. Evolutionary network analysis: A survey. ACM Computing Surveys, 47(1): 1–36. DOI: 10.1145/2601412
- Ahn, YY, Bagrow, JP and Lehmann, S. 2010. Link communities reveal multi-scale complexity in networks. Nature, 466: 761–764. DOI: 10.1038/nature09182
- Amelio, A and Pizzuti, C. 2014.
Overlapping Community Discovery Methods: A Survey . In: Gündüz-Öğüdücü, S and Etaner-Uyar, A (eds.), Social Networks: Analysis and Case Studies. Lecture Notes in Social Networks, 105–125. Springer, Vienna. DOI: 10.1007/978-3-7091-1797-2_6 - Bron, C and Kerbosch, J. 1973. Algorithm 457: Finding all cliques in an undirected graph, Community. ACM, 16(9): 575–577. DOI: 10.1145/362342.362367
- Clauset, A, Newman, ME and Moore, C. 2004. Finding community structure in very large networks. Physical Review E, 70(2):
066111 . DOI: 10.1103/PhysRevE.70.066111 - Conrad, L, Reid, F, McDaid, A and Hurley, N. 2010. Detecting highly overlapping community structure by greedy clique expansion. In: The 4th SNA-KDD Workshop’10, Washington, DC USA, 10.
July 25 . URL:http://hdl.handle.net/10197/2516 . - Cui, YZ, Wang, XY and Li, JQ. 2014. Detecting overlapping communities in networks using the maximal sub-graph and the clustering coefficient. Physica A: Statistical Mechanics and its Applications, 405: 85–91. DOI: 10.1016/j.physa.2014.03.027
- Delvenne, JC, Yaliraki, SN and Barahona, M. 2010. Stability of graph communities across time scales. Proceedings of the National Academy of Sciences, 29: 12755–12760. DOI: 10.1073/pnas.0903215107
- Fagnan, J, Zaïane, O and Barbosa, D. 2014. Using Triads to Identify Local Community Structure in Social Networks. In: 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), 108–112. Beijing, China,
August 17–20 . DOI: 10.1109/ASONAM.2014.6921568 - Fortunato, S. 2010. Community detection in graphs. Physics Reports, 486(3): 75–174. DOI: 10.1016/j.physrep.2009.11.002
- Fortunato, S and Castellano, C. 2012.
Community structure in graphs . In: Meyers, R (Eds.), Computational Complexity, 490–512. Springer, New York, NY. DOI: 10.1007/978-1-4614-1800-9 - Han, H and Tang, J. 2015. Probabilistic community and role model for social networks. In: Proceedings of the 21th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 407–416. Sydney, NSW, Australia.
- Lancichinetti, A, Fortunato, S and Radicchi, F. 2008. Benchmark graphs for testing community detection algorithms. Physical Review E, 78(4). DOI: 10.1103/PhysRevE.78.046110
- Lancichinetti, A, Fortunato, S and Skertész, J. 2009. Detecting the overlapping and hierarchical community structure in complex networks. New J. Phys, 11(3). DOI: 10.1088/1367-2630/11/3/033015
- Leskovec, L, Lang, KJ, Dasgupta, A and Mahoney, MW. 2008. Statistical properties of community structure in large social and information networks. In: The 17th International World Wide Web Conference, WWW’08), 695–704. Beijing, China.
April 21–25 . DOI: 10.1145/1367497.1367591 - Leskovec, J, Lang, KJ and Mahoney, M. 2010. Empirical comparison of algorithms for net- work community detection. In: Proceedings of the 19th International Conference on World Wide Web, 631–640. Raleigh, North Carolina, USA. DOI: 10.1145/1772690.1772755
- Liu, D, Jin, D, He, D, Huang, J, Yang, J and Yang, B. 2013. Community mining in complex networks. Journal of Computer Research & Development, 50(10): 2140–2154. URL:
http://crad.ict.ac.cn/EN/abstract/article_1338.shtml . - Lusseau, D, Schneider, K, Boisseau, OJ, Haase, P, Slooten, E and Dawson, SM. 2003. The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations-Can geographic isolation explain this unique trait. Behavioral Ecology and Sociobiology, 54(4): 396–405. DOI: 10.1007/s00265-003-0651-y
- McAuley, J and Leskovec, J. 2012. Learning to Discover Social Circles in Ego Networks. In: Advances in Neural Information Processing System 25 (NIPS 2012), curran associates, Inc., 539–547. URL:
http://papers.nips.cc/paper/4532-learning-to-discover-social-circles-in-ego-networks.pdf . - Mu, CH, Liu, Y, Wu, JS and Jiao, LC. 2014. Two-stage algorithm using influence coefficient for detecting the hierarchical, non-overlapping and overlapping community structure. Physica A: Statistical Mechanics and its Applications, 408: 47–61. DOI: 10.1016/j.physa.2014.04.023
- Newman, MEJ. 2006. Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23): 8577–8696. DOI: 10.1073/pnas.0601602103
- Palla, G, Derényi, I, Farkas, I and Vicsek, T. 2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043): 814–818. DOI: 10.1038/nature03607
- Peel, L, Larremore, DB and Clauset, A. 2017. The ground truth about metadata and community detection in networks. Science Advances, 3(5): 1–8. DOI: 10.1126/sciadv.1602548
- Pizzuti, C. 2018. Evolutionary Computation for Community Detection in Networks: A Review. IEEE Transactions on Evolutionary Computation, 22(3): 464–483. DOI: 10.1109/TEVC.2017.2737600
- Reichardt, J and Bornholdt, S. 2006. Statistical mechanics of community detection. Physical Review E, 74:
016110 . DOI: 10.1103/PhysRevE.74.016110 - Shen, HW, Cheng, XQ, Cai, K and Hu, MB. 2009. Detect overlapping and hierarchical community structure in networks. Physica A: Statistical Mechanics and its Applications, 38: 1706–1712. DOI: 10.1016/j.physa.2008.12.021
- Shi, C, Cai, Y, Fu, D, Dong, Y and Wu, B. 2013. A link clustering based overlapping community detection algorithm. Data Knowl. Eng., 87: 394–404. DOI: 10.1016/j.datak.2013.05.004
- Veldt, N, Gleich, DF and Wirth, A. 2018. A Correlation Clustering Framework for Community Detection. In: Proceedings of the 2018 World Wide Web Conference, 439–448. Lyon, France.
April 23–27 . DOI: 10.1145/3178876.3186110 - Wagenseller, P and Wang, F. 2018. Size Matters: A Comparative Analysis of Community Detection Algorithms. IEEE Transactions on Computational Social Systems, 1–10. DOI: 10.1109/TCSS.2018.2875626
- Wang, L. 2011. Using the relationship of shared neighbors to find hierarchical overlapping communities for effective connectivity in IoT. In: The 6th International Conference on Pervasive Computing and Applications, Port Elizabeth, 400–406. South Africa.
Oct. 26–28 . DOI: 10.1109/ICPCA.2011.6106538 - Xie, J, Kelley, S and Szymanski, BK. 2013. Overlapping community detection in net- works: The state-of-the-art and comparative study. ACM Comput. Surv. (CSUR), 45(4): 1–35. DOI: 10.1145/2501654.2501657
- Xie, JR, Szymanski, BK and Liu, XM. 2011. SLPA: Uncovering overlapping communities in social networks via a speaker–listener interaction dynamic process. In: The 11th IEEE International Conference on Data Mining Workshops, 344–349. Vancouver, BC, Canada.
Dec. 11–11 . DOI: 10.1109/ICDMW.2011.154 - Xu, Y, Xu, H, Zhang, D and Zhang, Y. 2016. Finding overlapping community from social networks based on community forest model. Knowledge-Based Systems, 109: 238–255. DOI: 10.1016/j.knosys.2016.07.007
- Ye, Q, Wu, B, Zhao, ZX and Wang, B. 2011. Detecting link communities in massive networks. In: The 2011 International Conference on Advances in Social Networks Analysis and Mining, 71–78. Kaohsiung, Taiwan.
July 25–27 . DOI: 10.1109/ASONAM.2011.53 - Zachary, WW. 1977. An information flow model for conflict and fission in small groups. Journal of Anthropological Research, 33(4): 452–473. DOI: 10.1086/jar.33.4.3629752
- Zhang, ZW and Wang, ZY. 2015. Mining overlapping and hierarchical communities in complex networks. Physica A: Statistical Mechanics and its Applications, 421: 25–33. DOI: 10.1016/j.physa.2014.11.023
- Zhao, Z, Zheng, S, Li, C, Sun, J, Chang, L and Chiclana, F. 2018. A comparative study on community detection methods in complex networks. Journal of Intelligent and Fuzzy Systems, 35(1): 1–10. DOI: 10.3233/JIFS-17682
