Community detection: Effective evaluation on large social networks

Journal of Complex Networks

Volumn 2, Issue 1, 2014, Pages 19-37

  Lee, Conrad ^a   Cunningham, Pádraig ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

Benchmarking; Community detection; Evaluation; Social networks

Indexed keywords

BENCHMARKING; METADATA; POPULATION DYNAMICS; SOCIAL NETWORKING (ONLINE);

CLASSIFICATION TASKS; COMMUNITY DETECTION; EVALUATING ALGORITHMS; EVALUATION; EVALUATION SCHEME; LARGE DATASETS; NETWORK COMMUNITIES; TELECOMMUNICATIONS SERVICES;

LARGE DATASET;

EID: 84960086762     PISSN: 20511310     EISSN: 20511329     Source Type: Journal    
DOI: 10.1093/comnet/cnt012     Document Type: Article

References (47)

1. Fortunato, S. (2010) Community detection in graphs. Phys. Rep., 486, 75-174.
2. Good, B. H., De Montjoye, Y.-A. & Clauset, A. (2010) Performance of modularity maximization in practical contexts. Phys. Rev. E, 81, 046106.
3. Lancichinetti, A., Kivelä, M., Saramäki, J. & Fortunato, S. (2010) Characterizing the community structure of complex networks. PLoS One, 5, e11976.
4. Yang, J. & Leskovec, J. (2012a) Defining and evaluating network communities based on ground-truth. Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics, p. 3. ACM.
5. Yang, J. & Leskovec, J. (2012b) Structure and overlaps of communities in networks. Proceedings of the 6th SNA-KDD Workshop.
6. Lancichinetti, A. & Fortunato, S. (2011) Limits of modularity maximization in community detection. Phys. Rev. E, 84, 066122.
7. Newman, M. E. & Girvan, M. (2004) Finding and evaluating community structure in networks. Phys. Rev. E, 69, 026113.
8. Berry, J. W., Hendrickson, B., LaViolette, R. A. & Phillips, C. A. (2011) Tolerating the community detection resolution limit with edge weighting. Phys. Rev. E, 83, 056119.
9. Fortunato, S. & Barthelemy, M. (2007) Resolution limit in community detection. Proc. Natl Acad. Sci., 104, 36-41.
10. Traud, A., Kelsic, E., Mucha, P. & Porter, M. (2011) Comparing community structure to characteristics in online collegiate social networks. SIAM Rev., 53, 526-543.
11. Traud, A. L., Mucha, P. J. & Porter, M. A. (2012) Social structure of Facebook networks. Phys. A, 391, 4165-4180.
12. Forsyth, E. & Katz, L. (1946) A matrix approach to the analysis of sociometric data: preliminary report. Sociometry, 9, 340-347.
13. Moreno, J. (1934) Who Shall Survive?: A New Approach to the Problem of Human Interrelations. Washington, D.C: Nervous and Mental Disease Publishing Co.
14. Davis, A., Gardner, B. & Gardner, M. (1941) Deep South. Chicago: University of Chicago Press.
15. Sampson, S. (1968) A novitiate in a period of change: an experimental and case study of social relationships. Ph.D. Thesis, Cornell University.
16. Zachary, W. W. (1977) An information flow model for conflict and fission in small groups. J. Anthropol. Res., 33, 452-473.
17. Freeman, L. C. (2003) Finding social groups: a meta-analysis of the southern women data. Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pp. 39-97. Washington, D.C: The National Academies Press.
18. Leskovec, J., Lang, K. J., Dasgupta, A. & Mahoney, M. W. (2009) Community structure in large networks: natural cluster sizes and the absence of large well-defined clusters. Internet Math., 6, 29-123.
19. Ahn, Y., Bagrow, J. & Lehmann, S. (2010) Link communities reveal multiscale complexity in networks. Nature, 466, 761-764.
20. Gregory, S. (2011) Fuzzy overlapping communities in networks. J. Stat. Mech. Theory Exp., 2011, P02017.
21. Lee, C., Reid, F., McDaid, A. & Hurley, N. (2010) Detecting highly overlapping community structure by greedy clique expansion. Proceedings of the 2010 SIGKDD Workshop on Social Network Mining and Analysis. New York: ACM, p. 11.
22. McDaid, A. & Hurley, N. (2010) Detecting highly overlapping communities with model-based overlapping seed expansion. International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2010, pp. 112-119. IEEE.
23. Reid, F., McDaid, A. & Hurley, N. (2011) Partitioning breaks communities. International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2011, pp. 102-109. IEEE.
24. Porter, M. A., Onnela, J.-P. & Mucha, P. J. (2009) Communities in networks. Notices Amer. Math. Soc., 56, 1082-1097.
25. Watts, D. J. (2004) The "new" science of networks. Annu. Rev. Sociol., 30, 243-270.
26. Clauset, A., Moore, C. & Newman, M. (2007) Structural inference of hierarchies in networks. Statistical Network Analysis: Models, Issues, and New Directions, Springer Berlin Heidelberg, pp. 1-13.
27. Duch, J. & Arenas, A. (2005) Community detection in complex networks using extremal optimization. Phys. Rev. E, 72, 027104.
28. Girvan, M. & Newman, M. (2002) Community structure in social and biological networks. Proc. Natl Acad. Sci., 99, 7821-7826.
29. Newman, M. (2006) Modularity and community structure in networks. Proc. Natl Acad. Sci., 103, 8577-8582.
30. Marras, E., Travaglione, A., Chaurasia, G., Futschik, M. & Capobianco, E. (2010) Inferring modules from human protein interactome classes. BMC Syst. Biol., 4, 102.
31. Condon, A. & Karp, R. M. (2001) Algorithms for graph partitioning on the planted partition model. Random Struct. Algor., 18, 116-140.
32. Lancichinetti, A. & Fortunato, S. (2009a) Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities. Phys. Rev. E, 80, 016118.
33. Lancichinetti, A., Fortunato, S. & Radicchi, F. (2008) Benchmark graphs for testing community detection algorithms. Phys. Rev. E, 78, 046110.
34. Lancichinetti, A. & Fortunato, S. (2009b) Community detection algorithms: a comparative analysis. Phys. Rev. E, 80, 056117.
35. Lee, C., Reid, F., McDaid, A. & Hurley, N. (2011) Seeding for pervasively overlapping communities. Phys. Rev. E, 83, 066107.
36. Xie, J., Kelley, S. & Szymanski, B. K. (2011) Overlapping community detection in networks: the state of the art and comparative study. Preprint arXiv:1110.5813.
37. Färber, I., Günnemann, S., Kriegel, H.-P., Kröger, P., Müller, E., Schubert, E., Seidl, T. & Zimek, A. (2010) On using class-labels in evaluation of clusterings. MultiClust: 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with KDD.
38. Blondel, V., Guillaume, J., Lambiotte, R. & Lefebvre, E. (2008) Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp., 2008, P10008.
39. Bishop, C. M. et al. (2006) Pattern Recognition and Machine Learning, vol. 1. New York: Springer.
40. Laumann, E. O., Marsden, P. V. & Prensky, D. (1989) The boundary specification problem in network analysis. Res. Methods Soc. Netw. Anal., 61, 87.
41. Rosvall, M. & Bergstrom, C. (2011) Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems. PloS One, 6, e18209.
42. Delvenne, J., Yaliraki, S. & Barahona, M. (2010) Stability of graph communities across time scales. Proc. Natl Acad. Sci., 107, 12755-12760.
43. Schaub, M. T., Lambiotte, R. & Barahona, M. (2012b) Encoding dynamics for multiscale community detection: Markov time sweeping for the map equation. Phys. Rev. E, 86, 026112.
44. Lichtenwalter, R., Lussier, J. & Chawla, N. (2010) New perspectives and methods in link prediction. Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 243-252. ACM.
45. Chierichetti, F., Kumar, R., Lattanzi, S., Mitzenmacher, M., Panconesi, A. & Raghavan, P. (2009) On compressing social networks. Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 219-228. ACM.
46. Pedregosa, F., Varoquaux, G., Gramfort, A.,Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M. & Duchesnay, E. (2011) Scikit-learn: machine learning in Python. J. Mach. Learn. Res., 12, 2825-2830.
47. Schaub, M., Delvenne, J., Yaliraki, S. & Barahona, M. (2012a) Markov dynamics as a zooming lens for multiscale community detection: non clique-like communities and the field-of-view limit. PloS One, 7, e32210.