Group profiling for understanding social structures

ACM Transactions on Intelligent Systems and Technology

Volumn 3, Issue 1, 2011, Pages

  Tang, Lei ^a   Xufei Wang, ^b   Huan Liu, ^b  

^a YAHOO INC   (United States)

^b Arizona State University   (United States)

Author keywords

Community; Group formation; Group profiling; Social media; Social structure

Indexed keywords

COMMUNITY; GROUP FORMATION; GROUP PROFILING; SOCIAL MEDIA; SOCIAL STRUCTURE;

DEVELOPING COUNTRIES; ELECTRIC NETWORK TOPOLOGY; USER INTERFACES; VISUALIZATION;

SOCIAL NETWORKING (ONLINE);

EID: 80155150191     PISSN: 21576904     EISSN: 21576912     Source Type: Journal    
DOI: 10.1145/2036264.2036279     Document Type: Article

References (51)

1. AGARWAL, N., LIU, H., TANG, L., AND YU, P. S. 2008. Identifying the influential bloggers in a community. In Proceedings of the International Conference on Web Search and Web Data Mining (WSDM'08). ACM, New York, 207-218.
2. AIRODI, E., BLEI, D., FIENBERG, S., AND XING, E. P. 2008. Mixed membership stochastic blockmodels. J. Mach. Learn. Res. 9, 1981-2014.
3. ALMACK, J. 1922. The influence of intelligence on the selection of associates. School Soc. 16, 529-530.
4. BACKSTROM, L., HUTTENLOCHER, D., KLEINBERG, J., AND LAN, X. 2006. Group formation in large social networks: Membership, growth, and evolution. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'06). ACM, New York, 44-54. (Pubitemid 44535502)
5. BAUMES, J., GOLDBERG, M.,MAGDON-ISMAIL, M., AND WALLACE, W. 2004. Discovering hidden groups in communication networks. In Proceedings of the 2nd NSF/NIJ Symposium on Intelligence and Security Informatics.
6. BLEI, D. M., NG, A. Y., AND JORDAN, M. I. 2003. Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993-1022.
7. BOTT, H. 1928. Observation of play activities in a nursery school. Genetic Psychol. Monographs 4, 44-88.
8. CHAKRABARTI, D. AND FALOUTSOS, C. 2006. Graph mining: Laws, generators, and algorithms. ACM Comput. Surv. 38, 1, 2. (Pubitemid 44029962)
9. CHANG, J., BOYD-GRABER, J., AND BLEI, D. M. 2009. Connections between the lines: Augmenting social networks with text. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09). ACM, New York, 169-178.
10. CHEN, W.-Y., CHU, J.-C., LUAN, J., BAI, H.,WANG, Y., AND CHANG, E. Y. 2009. Collaborative filtering for orkut communities: Discovery of user latent behavior. In Proceedings of the 18th International Conference on World Wide Web (WWW'09). ACM, New York, 681-690.
11. DUNNING, T. 1993. Accurate methods for the statistics of surprise and coincidence. Comput. Linguist. 19, 1, 61-74.
12. EROSHEVA, E., FIENBERG, S., AND LAFFERTY, J. 2004. Mixed-Membership models of scientific publications. Proc. Nat. Acad. Sci. 101, 90001, 5220-5227. (Pubitemid 38469130)
13. FIORE, A. T. AND DONATH, J. S. 2005. Homophily in online dating: When do you like someone like yourself? In CHI'05 Extended Abstracts on Human Factors in Computing Systems. ACM, New York, 1371-1374.
14. FORMAN, G. 2003. An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3, 1289-1305.
15. GUYON, I. 2003. An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157-1182.
16. HECHTER, M. 1988. Principles of Group Solidarity. University of California Press.
17. HOPCROFT, J., KHAN, O., KULIS, B., AND SELMAN, B. 2004. Tracking evolving communities in large linked networks. Proc. Nat. Acad. Sci. U.S.A. 101, 1, 5249-5253. (Pubitemid 38469134)
18. JACCARD, P. 1901. tude comparative de la distribution florale dans une portion des alpes et des jura. Bulletin de la Socit Vaudoise des Sciences Naturelles 37, 547-579.
19. JONES, K. S. 1972. A statistical interpretation of term specificity and its application in retrieval. J. Document. 28, 1, 1121.
20. KAMATH, K. AND CAVERLEE, J. 2011. Transient crowd discovery on the real-time social web. In Proceedings of the ACM Intenational Conference on Web Search and Data Mining (WSDM).
21. KELLY, J. AND ETLING, B. 2008. Mapping Iran's Online Public: Politics and Culture in the Persian Blogosphere. Berkman Center for Internet and Society at Harvard University.
22. KENDALL, M. 1938. A new measure of rank correlation. Biometrika 30, 81-89.
23. KUMAR, R., NOVAK, J., AND TOMKINS, A. 2006. Structure and evolution of online social networks. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'06). ACM, New York, 611-617. (Pubitemid 44535563)
24. LAUW, H. W., SHAFER, J. C., AGRAWAL, R., AND NTOULAS, A. 2010. Homophily in the digital world: A livejournal case study. IEEE Internet Comput. 14, 15-23.
25. LESKOVEC, J., KLEINBERG, J., AND FALOUTSOS, C. 2007. Graph evolution: Densification and shrinking diameters. ACM Trans. Knowl. Discov. Data 1, 1, 2.
26. LESKOVEC, J., BACKSTROM, L., KUMAR, R., AND TOMKINS, A. 2008a. Microscopic evolution of social networks. In Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08). ACM, New York, 462-470.
27. LESKOVEC, J., LANG, K. J., DASGUPTA, A., AND MAHONEY, M. W. 2008b. Statistical properties of community structure in large social and information networks. In Proceeding of the 17th International Conference on World Wide Web (WWW'08). ACM, New York, 695-704.
28. LIU, H. AND MOTODA, H. 1998. Feature Selection for Knowledge Discovery and Data Mining. Kluwer Academic Publishers.
29. LIU, Y.,NICULESCU-MIZIL, A., AND GRYC, W. 2009. Topic-Link lda: Joint modeling of topic and community for blog analysis. In Proceedins of the 26th International Conference on Machine Learning.
30. MACDONALD, C., SANTOS, R. L., OUNIS, I., AND SOBOROFF, I. 2010. Blog track research at trec. SIGIR Forum 44, 1, 57-74.
31. MCPHERSON, M., SMITH-LOVIN, L., AND COOK, J. M. 2001. Birds of a feather: Homophily in social networks. Ann. Rev. Sociol. 27, 415-444.
32. MEI, Q.,CAI, D., ZHANG, D., AND ZHAI, C. 2008. Topicmodeling with network regularization. In Proceeding of the 17th International Conference on World Wide Web (WWW'08). ACM, New York, 101-110.
33. NALLAPATI, R. M., AHMED, A., XING, E. P., AND COHEN, W. W. 2008. Joint latent topic models for text and citations. In Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08). ACM, New York, 542-550.
34. NEWMAN, M. 2003. The structure and function of complex networks. SIAM Review 45, 167-256.
35. PALLA, G., BARABASI, A.-L., AND VICSEK, T. 2007. Quantifying social group evolution. Nature 446, 7136, 664-667. (Pubitemid 46606882)
36. ROY, D. M., KEMP, C.,MANSINGHKA, V. K., AND TENENBAUM, J. B. 2006. Learning annotated hierarchies from relational data. In Proceedings of the Conference on Naval Information Processing System (NIPS). 1185-1192.
37. SHI, X., CHANG, K., NARAYANAN, V. K., JOSIFOVSKI, V., AND SMOLA, A. J. 2010. A compression framework for generating user profiles. In Proceedings of the ACM SIGIR Workshop on Feature Generation and Selection for Information Retrieval.
38. SHMUELI-SCHEUER, M., ROITMAN, H., CARMEL, D., MASS, Y., AND KONOPNICKI, D. 2010. Extracting user profiles from large scale data. In Proceedings of the Workshop on Massive Data Analytics on the Cloud (MDAC'10). ACM, New York, 4:1-4:6.
39. SUN, J., FALOUTSOS, C., PAPADIMITRIOU, S., AND YU, P. S. 2007. Graphscope: Parameter-free mining of large time-evolving graphs. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'07). ACM, New York, 687-696. (Pubitemid 350229254)
40. TANG, L. AND LIU, H. 2005. Bias analysis in text classification for highly skewed data. In Proceedings of the 5th IEEE International Conference on Data Mining (ICDM'05). IEEE Computer Society, 781-784. (Pubitemid 47385795)
41. TANG, L. AND LIU, H. 2009. Scalable learning of collective behavior based on sparse social dimensions. In Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM'09). 1107-1116.
42. TANG, L. AND LIU, H. 2010. Toward predicting collective behavior via social dimension extraction. IEEE Intell. Syst. 25, 19-25.
43. TANG, L., LIU, H., ZHANG, J., AGARWAL, N., AND SALERNO, J. J. 2008. Topic taxonomy adaptation for group profiling. ACM Trans. Knowl. Discov. Data 1, 4, 1-28.
44. TANTIPATHANANANDH, C., BERGER-WOLF, T., AND KEMPE, D. 2007. A framework for community identification in dynamic social networks. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). ACM, New York, NY, 717-726. (Pubitemid 350229257)
45. THELWALL, M. 2009. Homophily in myspace. J. Amer. Soc. Inf. Sci. Technol. 60, 2, 219-231.
46. WANG, X., TANG, L., GAO, H., AND LIU, H. 2010a. Discovering overlapping groups in social media. In Proceedings of the 10th IEEE International Conference on Data Mining.
47. WANG, Y., CONG, G., SONG, G., AND XIE, K. 2010b. Community-based greedy algorithm for mining topk influential nodes in mobile social networks. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10). ACM, New York, 1039-1048.
48. WASSERMAN, S. AND FAUST, K. 1994. Social Network Analysis: Methods and Applications. Cambridge University Press.
49. WATTS, D. AND DODDS, P. 2007. Influentials, networks, and public opinion formation. J. Consum. Res. 34, 4, 441-458.
50. WELLMAN, B. 1926. The school child's choice of companions. J. Educ. Res. 14, 126-132.
51. YANG, Y. AND PEDERSEN, J. O. 1997. A Comparative Study on Feature Selection in Text Categorization. Morgan Kaufmann Publishers, 412-420.