Learning to predict opinion share in social networks

Proceedings of the National Conference on Artificial Intelligence

Volumn 3, Issue , 2010, Pages 1364-1370

  Kimura, Masahiro ^a   Saito, Kazumi ^b   Ohara, Kouzou ^c   Motoda, Hiroshi ^d  

^a RYUKOKU UNIVERSITY   (Japan)

^b UNIVERSITY OF SHIZUOKA   (Japan)

^c AOYAMA GAKUIN UNIVERSITY   (Japan)

^d OSAKA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE;

COMPLETE NETWORKS; CORRECT SOLUTION; ION DIFFUSION; LINEAR EXTRAPOLATION; UPDATE ALGORITHMS; VOTER MODELS;

FORECASTING;

EID: 77958583891     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Agarwal, N., and Liu, H. 2008. Blogosphere: Research is sues, tools, and applications. SIGKDD Explorations 10:18-31.
2. Castellano, C; Munoz, M. A.; and Pastor-Satorras, R. 2009. Nonlinear q-voter model. Physical Review E 80:041129.
3. Chen, W.; Wang, Y.; and Yang, S. 2009. Efficient influ ence maximization in social networks. In Proceedings of KDD 2009, 199-208.
4. Crandall, D.; Cosley, D.; Huttenlocner, D.; Kleinberg, J.; and Suri, S. 2008. Feedback effects between similarity and sociai influence in online communities. In Proceedings of KDD 2008, 160-168.
5. Domingos, P., and Richardson, M. 2001. Mining the net work value of customers. In Proceedings of KDD 2001,57-66.
6. Even-Dar, E., and Shapria, A. 2007. A note on maximizing the spread of influence in social networks. In Proceedings of WINE 2007, 281-286.
7. Holme, P., and Newman, M. E. J. 2006. Nonequilibrium phase transition in the coevolution of networks and opinions. Physical Review E 74:056108.
8. Kempe, D.; Kleinberg, J.; and Tardos, E. 2003. Maximizing the spread of influence through a social network. In Pro ceedings of KDD 2003, 137-146.
9. Kimura, M.; Saito, K.; Nakano, R.; and Motoda, H. 2010. Extracting influential nodes on a social network for infor mation diffusion. Data Mining and Knowledge Discovery 20:70-97.
10. Kimura, M.; Saito, K.; and Motoda, H. 2009. Blocking links to minimize contamination spread in a social network. ACM Transactions on Knowledge Discovery from Data 3:9.
11. Leskovec, J.; Adamic, L. A.; and Huberman, B. A. 2007. The dynamics of viral marketing. ACM Transactions on the Web 1:5.
12. Liggett, T. M. 1999. Stochastic interacting systems: contact, voter, and exclusion processes. New York: Spriger.
13. Richardson, M., and Domingos, P. 2002. Mining knowledge-sharing sites for viral marketing. In Proceedings of KDD 2002, 61-70.
14. Sood, V., and Redner, S. 2005. Voter model on heteroge neous graphs. Physical Review Letters 94:178701.
15. Wu, F., and Huberman, B. A. 2008. How public opinion forms. In Proceedings of WINE 2008, 334-341.
16. Yang, H.; Wu, Z.; Zhou, C; Zhou, T.; and Wang, B. 2009. Effects of social diversity on the emergence of global con sensus in opinion dynamics. Physical Review E 80:046108.