Constant-factor approximation algorithms for identifying dynamic communities

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2009, Pages 827-835

  Tantipathananandh, Chayant ^a   Berger Wolf, Tanya ^a  

^a 1120 Science and Engineering Offices   (United States)

Author keywords

Approximation algorithms; Community identification; Dynamic social networks

Indexed keywords

APPROXIMATION FACTOR; BIPARTITE MATCHINGS; COMMUNITY IDENTIFICATION; COMMUNITY STRUCTURES; CONSTANT FACTOR APPROXIMATION; CONSTANT-FACTOR APPROXIMATION ALGORITHMS; DYNAMIC NETWORK; INPUT SIZE; PERFORMANCE GUARANTEES; REAL DATA SETS; SOCIAL INTERACTIONS; SOCIAL NETWORKS; STRUCTURE-BASED;

SOCIAL SCIENCES;

APPROXIMATION ALGORITHMS;

EID: 71049169334     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1557019.1557110     Document Type: Conference Paper

References (38)

1. J. Aizen, D. Huttenlocher, J. Kleinberg, and A. Novak. Traffic-based feedback on the web. Proc. National Academy of Sciences, 101(Suppl.1):5254-5260, 2004.
2. L. Backstrom, D. Huttenlocher, J. Kleinberg, and X. Lan. Group formation in large social networks: Membership, growth, and evolution. In Proc. 12th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2006.
3. J. Baumes, M. Goldberg, M. Magdon-Ismail, and W. Wallace. Discovering hidden groups in communication networks. In Proc. 2nd NSF/NIJ Symposium on Intelligence and Security Informatics, 2004.
4. T. Y. Berger-Wolf and J. Saia. A framework for analysis of dynamic social networks. In Proc. 12th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, pages 523-528, New York, NY, USA, 2006. ACM Press.
5. K. Carley and M. Prietula, editors. Computational Organization Theory. Lawrence Erlbaum associates, Hillsdale, NJ, 2001.
6. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. MIT Press, Cambridge, MA, USA, 2001.
7. D. P. Croft, R. James, P. Thomas, C. Hathaway, D. Mawdsley, K. Laland, and J. Krause. Social structure and co-operative interactions in a wild population of guppies (Poecilia reticulata). Behavioural Ecology and Sociobiology, In Press.
8. P. C. Cross, J. O. Lloyd-Smith, and W. M. Getz. Disentangling association patterns in fission-fusion societies using African buffalo as an example. Animal Behaviour, 69:499-506, 2005.
9. A. Davis, B. B. Gardner, and M. R. Gardner. Deep South. The University of Chicago Press, Chicago, IL, 1941.
10. R. Diestel. Graph Theory (Graduate Texts in Mathematics). Springer, August 2005.
11. N. Eagle and A. Pentland. Reality mining: Sensing complex social systems. J. Personal and Ubiquitous Computing, 2006.
12. I. R. Fischhoff, S. R. Sundaresan, J. Cordingley, H. M. Larkin, M.-J. Sellier, and D. I. Rubenstein. Social relationships and reproductive state influence leadership roles in movements of plains zebra (Equus burchellii). Animal Behaviour, 73: 825-831, 2007.
13. I. R. Fischhoff, S. R. Sundaresan, J. Cordingley, and D. I. Rubenstein. Habitat use and movements of plains zebra (Equus burchelli) in response to predation danger from lions. Behavioral Ecology, 18(4): 725-729, 2007.
14. G. Flake, S. Lawrence, C. L. Giles, and F. Coetzee. Self-organization and identification of web communities. IEEE Computer, 35(3), 2002.
15. D. Franzblau and A. Raychaudhuri. Optimal Hamiltonian completions and path covers for trees, and a reduction to maximum flow. Anziam journal, 44(2):193-204, 2002.
16. L. Freeman. Finding social groups: A meta-analysis of the southern women data. In R. Breiger, K. Carley, and P. Pattison, editors, Dynamic Social Network Modeling and Analysis. The National Academies Press, Washington, D.C., 2003.
17. L. C. Freeman. On the sociological concept of "group": a empirical test of two models. American Journal of Sociology, 98:152-166, 1993.
18. L. Getoor and C. Diehl. Link mining: A survey. SIGKDD Explorations Special Issue on Link Mining, 7(2), December 2005.
19. D. Gibson, J. M. Kleinberg, and P. Raghavan. Inferring web communities from link topology. In UK Conf. on Hypertext, pages 225-234, 1998.
20. M. Girvan and M. E. J. Newman. Community structure in social and biological networks. Proc. Natl. Acad. Sci., 99:8271-8276, 2002.
21. D. Gruhl, R. Guha, D. Liben-Nowell, and A. Tomkins. Information diffusion through blogspace. In Proc. 13th Intl. Conf. on World Wide Web, pages 491-501, New York, NY, USA, 2004. ACM Press.
22. J. Hopcroft, O. Khan, B. Kulis, and B. Selman. Natural communities in large linked networks. In Proc. 9th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, pages 541-546, 2003.
23. D. Kempe, J. Kleinberg, and E. Tardos. Maximizing the spread of influence through a social network. In Proc. 9th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2003.
24. J. Kleinberg and E. Tardos. Algorithm Design. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2005.
25. M. Kretzschmar and M. Morris. Measures of concurrency in networks and the spread of infectious disease. Math. Biosci., 133:165-195, 1996.
26. R. Kumar, P. Raghavan, S. Rajagopalan, and A. Tomkins. Trawling the web for emerging cyber-communities. In Proc. 8th Intl. World Wide Web Conf., May 1999.
27. M. Magdon-Ismail, M. Goldberg, W. Wallace, and D. Siebecker. Locating hidden groups in communication networks using hidden markov models. In Proc. Intl. Conf. on Intelligence and Security Informatics (ISI 2003), Tucson, AZ, 2003.
28. B. Malin. Data and collocation surveillance through location access patterns. In Proc. North American Association for Computational Social and Organizational Science Conf., Pittsburgh, PA, June 2004.
29. L. A. Meyers, M. Newman, and B. Pourbohloul. Predicting epidemics on directed contact networks. Journal of Theoretical Biology, 240:400-418, 2006.
30. M. Newman, A.-L. Barab'asi, and D. J. Watts, editors. The Structure and Dynamics of Networks. Princeton University Press, 2006.
31. J. M. Read and M. J. Keeling. Disease evolution on networks: the role of contact structure. Proc. R. Soc. Lond. B, 270:699-708, 2003.
32. E. M. Rogers. Diffusion of Innovations. Simon & Shuster, Inc., 5th edition, 2003.
33. D. I. Rubenstein, S. Sundaresan, I. Fischhoff, and D. Saltz. Social networks in wild asses: Comparing patterns and processes among populations. In A. Stubbe, P. Kaczensky, R. Samjaa, K. Wesche, and M. Stubbe, editors, Exploration into the Biological Resources of Mongolia, volume 10. Martin-Luther-University Halle-Wittenberg, 2007. In press.
34. J. Scott, R. Gass, J. Crowcroft, P. Hui, C. Diot, and A. Chaintreau. CRAWDAD trace cambridge/ haggle/ imote/ infocom (v. 2006-01-31). Downloaded from http://crawdad.cs.dartmouth.edu/cambridge/haggle/imote/infocom.
35. J. Sun, C. Faloutsos, S. Papadimitriou, and P. S. Yu. Graphscope: parameter-free mining of large time-evolving graphs. In Proc. 13th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, pages 687-696, New York, NY, USA, 2007. ACM.
36. S. R. Sundaresan, I. R. Fischhoff, J. Dushoff, and D. I. Rubenstein. Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager. Oecologia, 2006.
37. C. Tantipathananandh, T. Berger-Wolf, and D. Kempe. A framework for community identification in dynamic social networks. In ope: parameter-free mining of large time-evolving graphs. In Proc. 13th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, pages 717-726, New York, NY, USA, 2007. ACM.
38. S. Wasserman and F. K. Social Network Analysis. Cambridge University Press, Cambridge, MA, 1994.