Fast influence-based coarsening for large networks

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

Volumn , Issue , 2014, Pages 1296-1305

  Purohit, Manish ^b   Prakash, B Aditya ^a   Kang, Chanhyun ^b   Zhang, Yao ^a   Subrahmanian, V S ^b  

^a State University   (United States)

^b Department of Computer Science University of Maryland ^*  (United States)

Author keywords

coarsening; diffusion; graph mining; propagation

Indexed keywords

EID: 84907031422     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2623330.2623701     Document Type: Conference Paper

References (38)

1. R. M. Anderson and R. M. May. Infectious Diseases of Humans. Oxford University Press, 1991.
2. N. Bailey. The Mathematical Theory of Infectious Diseases and its Applications. Griffin, London, 1975.
3. S. Bikhchandani, D. Hirshleifer, and I. Welch. A theory of fads, fashion, custom, and cultural change in informational cascades. Journal of Political Economy, 100(5):992-1026, October 1992.
4. L. Briesemeister, P. Lincoln, and P. Porras. Epidemic profiles and defense of scale-free networks. WORM 2003, Oct. 27 2003.
5. M. Cha, A. Mislove, and K. P. Gummadi. A Measurement-driven Analysis of Information Propagation in the Flickr Social Network. In In Proceedings of the 18th International World Wide Web Conference (WWW'09), Madrid, Spain, April 2009.
6. D. Chakrabarti, Y. Wang, C. Wang, J. Leskovec, and C. Faloutsos. Epidemic thresholds in real networks. ACM TISSEC, 10(4), 2008.
7. W. Chen, C. Wang, and Y. Wang. Scalable influence maximization for prevalent viral marketing in large-scale social networks. KDD, 2010.
8. W. Chen, Y. Wang, and S. Yang. Efficient influence maximization in social networks. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 199-208. ACM, 2009.
9. I. S. Dhillon, Y. Guan, and B. Kulis. Weighted graph cuts without eigenvectors a multilevel approach. IEEE Trans. Pattern Anal. Mach. Intell., 29(11):1944-1957, 2007.
10. M. Elkin and D. Peleg. Approximating k-spanner problems for k> 2. Theoretical Computer Science, 337(1):249-277, 2005.
11. S. Eubank, H. Guclu, V. S. Anil Kumar, M. V. Marathe, A. Srinivasan, Z. Toroczkai, and N. Wang. Modelling disease outbreaks in realistic urban social networks. Nature, 429(6988):180-184, May 2004.
12. W. S. Fung, R. Hariharan, N. J. Harvey, and D. Panigrahi. A general framework for graph sparsification. In Proceedings of the 43rd annual ACM symposium on Theory of computing, pages 71-80. ACM, 2011.
13. A. Ganesh, L. Massoulié, and D. Towsley. The effect of network topology on the spread of epidemics. In IEEE INFOCOM, Los Alamitos, CA, 2005. IEEE Computer Society Press.
14. J. Goldenberg, B. Libai, and E. Muller. Talk of the network: A complex systems look at the underlying process of word-of-mouth. Marketing Letters, 2001.
15. A. Goyal, F. Bonchi, and L. V. Lakshmanan. Learning influence probabilities in social networks. WSDM '10, 2010.
16. A. Goyal, W. Lu, and L. V. S. Lakshmanan. Simpath: An efficient algorithm for influence maximization under the linear threshold model. ICDM, 2011.
17. M. Granovetter. Threshold models of collective behavior. Am. Journal of Sociology, 83(6):1420-1443, 1978.
18. D. Gruhl, R. Guha, D. Liben-Nowell, and A. Tomkins. Information diffusion through blogspace. In WWW '04, 2004.
19. Y. Hayashi, M. Minoura, and J. Matsukubo. Recoverable prevalence in growing scale-free networks and the effective immunization. arXiv:cond-mat/ 0305549 v2, Aug. 6 2003.
20. H. W. Hethcote. The mathematics of infectious diseases. SIAM Review, 42, 2000.
21. G. Karypis and V. Kumar. METIS: Unstructured graph partitioning and sparse matrix ordering system. The University of Minnesota, 2, 1995.
22. D. Kempe, J. Kleinberg, and E. Tardos. Maximizing the spread of influence through a social network. In KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 137-146, New York, NY, USA, 2003. ACM.
23. J. O. Kephart and S. R. White. Measuring and modeling computer virus prevalence. IEEE Computer Society Symposium on Research in Security and Privacy, 1993.
24. M. Kimura and K. Saito. Tractable models for information diffusion in social networks. Knowledge Discovery in Databases: PKDD 2006, pages 259-271, 2006.
25. R. Kumar, J. Novak, P. Raghavan, and A. Tomkins. On the bursty evolution of blogspace. In WWW '03: Proceedings of the 12th international conference on World Wide Web, pages 568-576, New York, NY, USA, 2003. ACM Press.
26. T. Lappas, E. Terzi, D. Gunopulos, and H. Mannila. Finding effectors in social networks. In Proceedings of the 16th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Washington, DC, pages 1059-1068, 2010.
27. J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, and N. S. Glance. Cost-effective outbreak detection in networks. In KDD, pages 420-429, 2007.
28. M. Mathioudakis, F. Bonchi, C. Castillo, A. Gionis, and A. Ukkonen. Sparsification of influence networks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 529-537. ACM, 2011.
29. A. G. McKendrick. Applications of mathematics to medical problems. In Proceedings of Edin. Math. Society, volume 44, pages 98-130, 1925.
30. Y. Mehmood, N. Barbieri, F. Bonchi, and A. Ukkonen. Csi: Community-level social influence analysis. In Machine Learning and Knowledge Discovery in Databases, volume 8189 of Lecture Notes in Computer Science. 2013.
31. R. Pastor-Santorras and A. Vespignani. Epidemic spreading in scale-free networks. Physical Review Letters 86, 14, 2001.
32. B. A. Prakash, D. Chakrabarti, M. Faloutsos, N. Valler, and C. Faloutsos. Threshold conditions for arbitrary cascade models on arbitrary networks. In ICDM, 2011.
33. B. A. Prakash, J. Vreeken, and C. Faloutsos. Spotting culprits in epidemics: How many and which ones? In ICDM, 2012.
34. M. Richardson and P. Domingos. Mining knowledge-sharing sites for viral marketing. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 61-70. ACM, 2002.
35. E. M. Rogers. Diffusion of Innovations, 5th Edition. Free Press, August 2003.
36. P. Shakarian, M. Broecheler, V. Subrahmanian, and C. Molinaro. Using generalized annotated programs to solve social network optimization problems. ACM Transactions on Computational Logic, 2012.
37. H. Tong, B. A. Prakash, T. Eliassi-Rad, M. Faloutsos, and C. Faloutsos. Gelling, and melting, large graphs by edge manipulation. In ACM CIKM, 2012.
38. H. Tong, B. A. Prakash, C. E. Tsourakakis, T. Eliassi-Rad, C. Faloutsos, and D. H. Chau. On the vulnerability of large graphs. In ICDM, 2010.