Anti-modularity and anti-community detecting in complex networks

Information Sciences

Volumn 275, Issue , 2014, Pages 293-313

  Chen, Ling ^a,b   Yu, Qiang ^a   Chen, Bolun ^a  

^a YANGZHOU UNIVERSITY   (China)

^b NANJING UNIVERSITY   (China)

Author keywords

Anti community structure; Anti modularity; Bipartite graph; Graph; Network

Indexed keywords

NETWORKS (CIRCUITS); SOCIAL SCIENCES;

ANTI-MODULARITY; BIPARTITE GRAPHS; GRAPH; LABEL PROPAGATION; QUANTITATIVE MEASURES; REAL-WORLD NETWORKS; SOCIAL RESEARCH;

ALGORITHMS;

EID: 84900813410     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.02.040     Document Type: Article

References (52)

1. N. Alon, and B. Sudakov Bipartite subgraph and the smallest eigenvalue Combinat. Probab. Comput. 9 2000 1 12
2. S.O. Aral, J.P. Hughes, B. Stoner, W. Whittington, H.H. Handsfield, R.M. Anderson, and K.K. Holmes Sexual mixing patterns in the spread of gonococcal and chlamydial infections Am. J. Public Health 89 1999 825 833
3. J.P. Bagrow Evaluating local community methods in networks J. Stat. Mech. 2008 P05001
4. S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, and D.U. Hwang Complex networks: structure and dynamics Phys. Rep. 424 2006 175 308
5. U. Brandes, D. Delling, M. Gaertler, R. Görke, M. Hoefer, Z. Nikoloski, D. Wagner, On finding graph clusterings with maximum modularity. in: Proc. 33rd Intl. Workshop Graph-Theoretic Concepts in Computer Science (WG'07), LNCS, vol. 4769, 2007, pp. 121-132.
6. D.B. Chen, M.S. Shang, Z.H. Lv, and Y. Fu Detecting overlapping communities of weighted networks via a local algorithm Physica A 389 19 2010 4177 4187
7. X.Q. Cheng, F.X. Ren, S. Zhou, and M.B. Hu Triangular clustering in document networks New J. Phys. 11 3 2009 033019
8. X.Q. Cheng, F.X. Ren, H.W. Shen, Z.K. Zhang, and T. Zhou Bridgeness: a local index on edge significance in maintaining global connectivity J. Stat. Mech. 2010 P10011
9. L. Danon, A. DÍIaz-Guilera, J. Duch, and A. Arenas Comparing community structure identification J. Stat. Mech. 2005 P09008
10. L. Danon, J. Duch, A. Diaz-Guilera, and A. Arenas J. Stat. Mech. 2005 P09008
11. J. Duch, and A. Arenas Community detection in complex networks using extremal optimization Phys. Rev. E 72 2 2005 027104
12. A. Davis, B.B. Gardner, and M.R. Gardner Deep South 1941 University of Chicago Press
13. E. Estrada, and J.A. Rodriguez-Velazquez Spectral measures of bipartivity in complex networks Phys. Rev. E 72 2005 046105
14. G.W. Flake, S. Lawrence, C.L. Giles, and F.M. Coetzee Self organization and identification of Web communities Computer 35 3 2002 66 71
15. S. Fortunato Community detection in graphs Phys. Rep. 486 3-5 2010 75 174
16. G.P. Garnett, J.P. Hughes, R.M. Anderson, B.P. Stoner, S.O. Aral, W.L. Whittington, H.H. Handsfield, and K.K. Holmes Sexual mixing patterns of patients attending sexually transmitted diseases clinics Sex. Transmit. Dis. 23 1996 248 257
17. M. Girvan, and M.E.J. Newman Community structure in social and biological networks Proc. Natl. Acad. Sci. USA 99 12 2002 7821 7826
18. M. Goemans, and D. Williamson Improved approximation algorithms for maximum cut and satisability problems using semidefinite programming J. Assoc. Comput. Mach. 42 1995 1115 1145
19. R. Guimer'a, and L.A. Nunes Amaral Functional cartography of complex metabolic networks Nature 433 2005 895 900
20. P. Holme, F. Liljeros, C.R. Edling, and B.J. Kim Net-work bipartivity Phys. Rev. E 68 2003 056107
21. http://vlado.fmf.uni-lj.si/pub/networks/data/.
22. H. Jeong et al. Nature (London) 407 2000 651
23. J.M. Kleinberg Authoritative sources in a hyperlinked environment J. ACM 46 1999 604 632
24. J. Leskovec, K.J. Lang, A. Dasgupta, M.W. Mahoney, Statistical properties of community structure in large social and information networks, in: Proc. 17th Int'l Conf. World Wide Web (WWW'08), 2008, pp. 695-704.
25. J. Leskovec, K.J. Lang, M.W. Mahoney, Empirical comparison of algorithms for network community detection, in: Proc. 19th Int'l Conf. World Wide Web (WWW'10), 2010, pp. 631-640.
26. W.Y. Li Revealing network communities with a nonlinear programming method Inform. Sci. 229 2013 18 28
27. P.D. Meo, E. Ferrara, G. Fiumara, and A. Provetti Enhancing community detection using a network weighting strategy Inform. Sci. 222 2013 648 668
28. B. Mirkin, and S. Nascimento Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices Inform. Sci. 183 1 2012 16 34
29. S.A. Morris, cond-mat/0501386v1, 2005.
30. M.E.J. Newman Modularity and community structure in networks Proc. Natl. Acad. Sci. USA 103 23 2006 8577 8582
31. M.E.J. Newman Finding community structure in networks using the eigenvectors of matrices Phys. Rev. E 74 3 2006 036104
32. M.E.J. Newman The structure and function of complex networks SIAM Rev. 45 2 2003 167 256
33. M.E.J. Newman, and M. Girvan Finding and evaluating community structure in networks Phys. Rev. E 69 2 2004 026113
34. M.E. Newman, and E.A. Leicht Mixture models and exploratory analysis in networks Proc. Natl. Acad. Sci. USA 104 23 2007 9564 9569
35. A.Y. Ng, M.I. Jordan, Y. Weiss, On spectral clustering: analysis and an algorithm, in: Advance in Neural Information Processing Systems, vol. 14, 2001.
36. G. Palla, I. DerÍenyi, I. Farkas, and T. Vicsek Uncovering the overlapping community structure of complex networks in nature and society Nature 435 2005 814 818
37. F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi Defining and identifying communities in networks Proc. Natl. Acad. Sci. USA 101 9 2004 2658 2663
38. U.N. Raghavan, R. Albert, and S. Kumara Near linear time algorithm to detect community structures in large-scale networks Phys. Rev. E 76 3 2007 036106 10.1103/PhysRevE.76.036106
39. M. Rosvall, and C.T. Bergstrom Maps of random walks on complex networks reveal community structure Proc. Natl. Acad. Sci. USA 105 4 2008 1118 1123
40. J. Scott Social Network Analysis: A handbook second ed. 2000 Sage Publication London pp. 454-529
41. H.W. Shen, and X.Q. Cheng Spectral methods for the detection of network community structure: a comparative analysis J. Stat. Mech. 2010 P10020
42. H.W. Shen, X.Q. Cheng, K. Cai, and M.B. Hu Detect overlapping and hierarchical community structure in networks Physica A 388 8 2009 1706 1712
43. H.W. Shen, X.Q. Cheng, and J.F. Guo Quantifying and identifying the overlapping community structure in networks J. Stat. Mech. 2009 P07042
44. S.A. Souma, Y. Fujiwara, and H. Aoyama Physica A 324 2003 396
45. P.G. Sun, L. Gao, and S.S. Han Identification of overlapping and non-overlapping community structure by fuzzy clustering in complex networks Inform. Sci. 181 6 2011 1060 1071
46. P.G. Sun, L. Gao, and Y. Yang Maximizing modularity intensity for community partition and evolution Inform. Sci. 236 2013 83 92
47. L. Trevisan, Max cut and the smallest eigenvalue, in: Proceedings of STOC'09.
48. F. Wang, Detecting Anti-communities of Networks Based on Spectral Method, Thesis for the Master Degree, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China, June 2008.
49. S. Wasserman, and K. Faust Social Network Analysis 1994 Cambridge University Press Cambridge, UK
50. S. White, P. Smyth, A spectral clustering approach to finding communities in graphs, in: H. Kargupta, J. Srivastava, C. Kamath, A. Goodman (Eds.), Proceedings of the 5th SIAM International Conference on Data Mining, 2005.
51. B. Yang, W.K. Cheung, and J.M. Liu Community mining from signed social networks IEEE Trans. Knowl. Data Eng. 19 10 2007 1333 1348
52. J. Scott, and M. Hughes The Anatomy of Scottish Capital: Scottish Companies and Scottish Capital, 1900-1979 1980 CroomHelm London