A multi-source integration framework for user occupation inference in social media systems

World Wide Web

Volumn 18, Issue 5, 2015, Pages 1247-1267

  Huang, Yanxiang ^a   Yu, Lele ^a   Wang, Xiang ^a   Cui, Bin ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Feature selection; Multi source integration; Occupation inference; Social network; User profile modeling

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPLEX NETWORKS; EMPLOYMENT; FEATURE EXTRACTION; INTERNET; LEARNING SYSTEMS; WEBSITES;

COMMUNITY DISCOVERIES; COMMUNITY STRUCTURES; MACHINE LEARNING CLASSIFICATION; MULTI-SOURCE INTEGRATIONS; OCCUPATION INFERENCE; SOCIAL MEDIA SYSTEMS; SOCIAL NETWORK INFORMATIONS; USER PROFILE MODEL;

SOCIAL NETWORKING (ONLINE);

EID: 84939651806     PISSN: 1386145X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11280-014-0300-6     Document Type: Article

References (30)

1. Ahn, D., Kim, T.J., Hyun, S., Lee, D.: Inferring user interest using familiarity and topic similarity with social neighbors in facebook. In: Proceedings of the 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology, pp. 196–200. IEEE (2012)
2. Backstrom, L., Sun, E., Marlow, C.: Find me if you can: improving geographical prediction with social and spatial proximity. In: Proceedings of the 19th international conference on World wide web, pp. 61–70. ACM (2010)
3. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. mach. Learn. res. 3, 993–1022 (2003)
4. Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.P.: Measuring user influence in twitter: The million follower fallacy. In: Proceedings of the 4th international aaai conference on weblogs and social media (icwsm), pp. 10–17. AAAI (2010)
5. Choudhury, M.D., Gamon, M., Counts, S., Horvitz, E.: predict depression from social media. In: Proceedings of the 17th international AAAI conference on Webblogs and Social Media, pp. 128–137. AAAI (2013)
6. Clauset, A., Newman, M.E., Moore, C.: Finding community structure in very large networks. Phys. rev. E 70 (6), 066–111 (2004)
7. Conover, M.D., Ratkiewicz, J., Francisco, M., Gonċalves, B., Flammini, A., Menczer, F.: Political polarization on twitter. In: Proceedings 5th Intl. Conference on Weblogs and Social Media (2011)
8. Girvan, M., Newman, M.E.: Community structure in social and biological networks, Vol. 99 (2002)
9. Hagen, L., Kahng, A.B.: New spectral methods for ratio cut partitioning and clustering. Comput.-aided des. Integr. Circ. syst., ieee trans. 11 (9), 1074–1085 (1992)
10. Han, J.: Mining heterogeneous information networks by exploring the power of links. In: Discovery Science, pp. 13–30. Springer (2009)
11. Hofmann, T.: Probabilistic latent semantic analysis. In: Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence, pp. 289–296. Morgan Kaufmann Publishers Inc (1999)
12. Li, R., Wang, S., Deng, H., Wang, R., Chang, K.C.C.: Towards social user profiling: unified and discriminative influence model for inferring home locations. In: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 1023–1031. ACM (2012)
13. McAuley, J., Leskovec, J.: From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews. In: Proceedings of the 22th international conference on World Wide Web, pp. 897–908. ACM (2013)
14. McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: Homophily in social networks. Annu. Rev. Sociol., 415–444 (2001)
15. Mislove, A., Viswanath, B., Gummadi, K.P., Druschel, P.: You are who you know: inferring user profiles in online social networks. In: Proceedings of the third ACM international conference on Web search and data mining, pp. 251–260. ACM (2010)
16. Newman, M.E.: Finding community structure in networks using the eigenvectors of matrices. Phys. rev. E 74 (3), 036–104 (2006)
17. Newman, M.E.: Modularity and community structure in networks. Proc. Natl. Acad. Sci. 103 (23), 8577–8582 (2006)
18. Otterbacher, J.: Inferring gender of movie reviewers: exploiting writing style, content and metadata. In: Proceedings of the 19th ACM international conference on Information and knowledge management, pp. 369–378. ACM (2010)
19. Pennacchiotti, M., Popescu, A.M.: Democrats, republicans and starbucks afficionados: user classification in twitter. In: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 430–438. ACM (2011)
20. Pothen, A., Simon, H.D., Liou, K.P.: Partitioning sparse matrices with eigenvectors of graphs. SIAM J. Matrix Anal. Appl. 11 (3), 430–452 (1990)
21. Rao, D., Yarowsky, D., Shreevats, A., Gupta, M.: Classifying latent user attributes in twitter. In: Proceedings of the 2nd international workshop on Search and mining user-generated contents, pp. 37–44. ACM (2010)
22. Sen, P., Namata, G., Bilgic, M., Getoor, L., Galligher, B., Eliassi-Rad, T.: Collective classification in network data. AI mag. 29 (3), 93 (2008)
23. Sun, Y., Norick, B., Han, J., Yan, X., Yu, P.S., Yu, X.: Integrating meta-path selection with user-guided object clustering in heterogeneous information networks. In: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 1348–1356. ACM (2012)
24. Tang, L., Liu, H.: Relational learning via latent social dimensions. In: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 817–826. ACM (2009)
25. Tinati, R., Carr, L., Hall, W., Bentwood, J.: Identifying communicator roles in twitter. In: Proceedings of the 21st international conference companion on World Wide Web, pp. 1161–1168. ACM (2012)
26. Wang, X., Yu, L., Yao, J., Cui, B.: A multiple feature integration to infer occupation from social media records. In: Proceedings of the 14th international conference on Web Information Systems Engineering, pp. 137–150. Springer (2013)
27. Weinsberg, U., Bhagat, S., Ioannidis, S., Taft, N.: Blurme: inferring and obfuscating user gender based on ratings. In: Proceedings of the sixth ACM conference on Recommender systems, pp. 195–202. ACM (2012)
28. Wen, Z., Lin, C.Y.: Improving user interest inference from social neighbors. In: Proceedings of the 20th ACM international conference on Information and knowledge management, pp. 1001–1006. ACM (2011)
29. Yang, S.H., Long, B., Smola, A., Sadagopan, N., Zheng, Z., Zha, H.: Like like alike: joint friendship and interest propagation in social networks. In: Proceedings of the 20th international conference on World wide web, pp. 537–546. ACM (2011)
30. Zuo, Y., Wang, J., You, F.: Personal user or organizational user? behavior on microblog can tell. In: Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining, pp. 706–707. IEEE (2012)