Community detection plays an important role in the analysis of complex networks. However, overlapping community detection in real networks is still a challenge. To address the problems of pre-input parameters and label redundancy, an improved label propagation algorithm (ILPA) that adopts a method based on the influence factor is proposed in this paper. Theoretical analysis and experimental results on both synthetic and real datasets show that the ILPA detects that the overlapping community has higher accuracy compared to other existing methods.
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Fortunato S (2010) Community detection in graphs. Phys Rep 486(3):75–174
Huang J, Sun H, Liu Y, Song Q, Weninger T (2011) Towards online multiresolution community detection in large-scale networks. PLoS ONE 6(8):e23829
Xie J, Kelley S, Szymanski BK (2013) Overlapping community detection in networks: the state-of-the-art and comparative study. ACM Comput Surv (csur) 45(4):43
Raghavan UN, Albert R, Kumara S (2007) Near linear time algorithm to detect community structures in large-scale networks. Phys Rev E 76(3):036106
Barber MJ, Clark JW (2009) Detecting network communities by propagating labels under constraints. Phys Rev E 80(2):026129
Liu X, Murata T (2010) Advanced modularity-specialized label propagation algorithm for detecting communities in networks. Physica A Stat Mech Appl 389(7):1493–1500
Palla G, Dernyi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435:814–818
Gregory S (2010) Finding overlapping communities in networks by label propagation. New J Phys 12(10):103018
Xie J, Szymanski BK, Liu X (2011) Slpa: uncovering overlapping communities in social networks via a speaker-listener interaction dynamic process. In: 2011 IEEE 11th international conference on data mining workshops. IEEE, pp 344–349
He-Li S, Jian-Bin H, Yong-Qiang T, Qin-Bao S, Huai-Liang L (2015) Detecting overlapping communities in networks via dominant label propagation. Chin Phys B 24(1):018703
Chakrabarti D, Kumar R, Tomkins A (2006) Evolutionary clustering. In: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, pp 554–560
Chi Y, Song X, Zhou D, Hino K, Tseng BL (2007) Evolutionary spectral clustering by incorporating temporal smoothness. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 153–162
Lin Y-R, Chi Y, Zhu S, Sundaram H, Tseng BL (2008) Facetnet: a framework for analyzing communities and their evolutions in dynamic networks. In: Proceedings of the 17th international conference on World Wide Web. ACM, pp 685–694
Kim M-S, Han J (2009) A particle-and-density based evolutionary clustering method for dynamic networks. Proc VLDB Endow 2(1):622–633
Nguyen NP, Dinh TN, Tokala S, Thai MT (2011) Overlapping communities in dynamic networks: their detection and mobile applications. In: Proceedings of the 17th annual international conference on mobile computing and networking. ACM, pp 85–96
Cazabet R, Amblard F, Hanachi C (2010) Detection of overlapping communities in dynamical social networks. In: 2010 IEEE second international conference on social computing (SocialCom). IEEE, pp 309–314
Tang L, Liu H, Zhang J, Nazeri Z (2008) Community evolution in dynamic multi-mode networks. In: Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, pp 677–685
Yang T, Chi Y, Zhu S, Gong Y, Jin R (2011) Detecting communities and their evolutions in dynamic social networksa Bayesian approach. Mach Learn 82(2):157–189
Gupta M, Aggarwal CC, Han J, Sun Y (2001) Evolutionary clustering and analysis of bibliographic networks. In: 2011 International conference on advances in social networks analysis and mining (ASONAM). IEEE, pp 63–70
Tantipathananandh C, Berger-Wolf TY (2011) Finding communities in dynamic social networks. In: 2011 IEEE 11th international conference on data mining. IEEE, pp 1236–1241
Li Y, He K, Kloster K, Bindel D, Hopcroft J (2018) Local spectral clustering for overlapping community detection. ACM Trans Knowl Discov Data 12(2):17:1–17:27
Shi P, He K, Bindel D, Hopcroft JE (2019) Locally-biased spectral approximation for community detection. Knowl Based Syst 164:459–472
Chin JH, Ratnavelu K (2016) Detecting community structure by using a constrained label propagation algorithm. PLos ONE 11:1–21. https://doi.org/10.1371/journal.pone.0155320
Chin JH, Ratnavelu KA (2017) Semi-synchronous label propagation algorithm with constraints for community detection in complex networks. Sci Rep 7:45836
Xu M, Li Y, Li R, Zou F, Gu X (2019) Eadp: an extended adaptive density peaks clustering for overlapping community detection in social networks. Neurocomputing 337:287–302
Chakraborty T, Ghosh S, Park N (2019) Ensemble-based overlapping community detection using disjoint community structures. Knowl Based Syst 163:241–251
Newman ME (2004) Detecting community structure in networks. Eur Phys J B Condens Matter Complex Syst 38(2):321–330
Lü L, Zhang Y-C, Yeung CH, Zhou T (2011) Leaders in social networks, the delicious case. PLoS ONE 6(6):e21202
Lancichinetti A, Fortunato S, Radicchi F (2008) Benchmark graphs for testing community detection algorithms. Phys Rev E 78(4):046110
Lusseau D (2003) The emergent properties of a dolphin social network. Proc R Soc Lond B Biol Sci 270(Suppl 2):S186–S188
Lusseau D, Newman ME (2004) Identifying the role that animals play in their social networks. Proc R Soc Lond B Biol Sci 271(Suppl 6):S477–S481
Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33:452–473
Girvan M, Newman ME (2002) Community structure in social and biological networks. Proc Natl Acad Sci 99(12):7821–7826
Lancichinetti A, Fortunato S, Kertész J (2009) Detecting the overlapping and hierarchical community structure in complex networks. New J Phys 11(3):033015
Nicosia V, Mangioni G, Carchiolo V, Malgeri M (2009) Extending the definition of modularity to directed graphs with overlapping communities. J Stat Mech Theory Exp 2009(03):P03024
Shen H, Cheng X, Cai K, Hu M-B (2009) Detect overlapping and hierarchical community structure in networks. Physica A Stat Mech Appl 388(8):1706–1712
This paper is supported by Project supported by Key Scientific and Technological Research Projects in Henan Province (Grand No. 192102210125) and in part by the Study Abroad Activities of Science and Technology Project of Henan Province. In addition, the authors also will thank the anonymous reviewers for their comments and suggestions.
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Dong, S. Improved label propagation algorithm for overlapping community detection. Computing 102, 2185–2198 (2020). https://doi.org/10.1007/s00607-020-00836-3
- Overlapping community
- Community detection
- Label propagation
- Complex network
Mathematics Subject Classification