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Issue No.04 - July/August (2010 vol.25)
pp: 19-25
Lei Tang , Arizona State University, Tempe
<p>The social-dimension-based learning framework (SocioDim) can help predict online behaviors of social media users given a network and the behavior information of some actors in the network.</p>
behavior prediction, collective behavior, social dimensions, social media, edge-centric clustering, node-centric clustering, intelligent systems
Lei Tang, "Toward Predicting Collective Behavior via Social Dimension Extraction", IEEE Intelligent Systems, vol.25, no. 4, pp. 19-25, July/August 2010, doi:10.1109/MIS.2010.36
1. M. McPherson, L. Smith-Lovin, and J.M. Cook, "Birds of a Feather: Homophily in Social Networks," Ann. Rev. of Sociology, vol. 27, 2001, pp. 415–444.
2. M. Granovetter, "Threshold Models of Collective Behavior," Am. J. Sociology, vol. 83, no. 6, 1978, p. 1420.
3. T.C. Schelling, "Dynamic Models of Segregation," J. Mathematical Sociology, vol. 1, 1971, pp. 143–186.
4. S.A. Macskassy and F. Provost, "Classification in Networked Data: A Toolkit and a Univariate Case Study," J. Machine Learning Research, vol. 8, no. 5, 2007, pp. 935–983.
5. L. Tang and H. Liu, "Relational Learning via Latent Social Dimensions," Proc. 15th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD 09), ACM Press, 2009, pp. 817–826.
6. M. Newman, "Finding Community Structure in Networks Using the Eigenvectors of Matrices," Physical Rev. E (Statistical, Nonlinear, and Soft Matter Physics), vol. 74, no. 3, 2006.
7. L. Tang and H. Liu, "Scalable Learning of Collective Behavior Based on Sparse Social Dimensions," Proc. 18th ACM Conf. Information and Knowledge Management (CIKM 09), ACM Press, 2009, pp. 1107–1116.
8. M. Newman, "Power Laws, Pareto Distributions and Zipf's Law," Contemporary Physics, vol. 46, no. 5, 2005, pp. 323–352.
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