Hashtag Graph Based Topic Model for Tweet Mining

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn 2015-January, Issue January, 2014, Pages 1025-1030

  Wang, Yuan ^a   Liu, Jie ^a   Qu, Jishi ^a   Huang, Yalou ^a   Chen, Jimeng ^a   Feng, Xia ^b  

^a NANKAI UNIVERSITY   (China)

^b CIVIL AVIATION UNIVERSITY OF CHINA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

GRAPHIC METHODS; SEMANTICS; SOCIAL NETWORKING (ONLINE); STATISTICS;

EFFECTIVE SOLUTION; LARGE VOCABULARY; LATENT DIRICHLET ALLOCATION; LATENT VARIABLE; RELATION INFORMATION; SEMANTIC RELATIONS; SEMI-STRUCTURED; STATE OF THE ART;

DATA MINING;

EID: 84936930203     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2014.60     Document Type: Conference Paper

References (14)

1. Y. Chen, H. Amiri, Z. Li, and T.-S. Chua, "Emerg ing topic detection for organizations from microblogs," in Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, ser. SIGIR '13. New York, NY, USA: ACM, 2013, pp. 43-52.
2. R. Mehrotra, S. Sanner, W. Buntine, and L. Xie, " Improving lda topic models for microblogs via tweet pooling and automatic labeling," in Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, ser. SIGIR '13. New York, NY, USA: ACM, 2013, pp. 889-892.
3. X. Yan, J. Guo, Y. Lan, and X. Cheng, "A biterm topic model for short texts, " in Proceedings of the 22Nd International Conference on World Wide Web, ser. WWW '13. Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee, 2013, pp. 1445-1456.
4. T. Hofmann, "Pro babilistic latent semantic indexing," in Proceedings of the 22Nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ser. SIGIR '99. New York, NY, USA: ACM, 1999, pp. 50-57.
5. D. M. Blei, A. Y. Ng, and M. I. Jordan, "Latent dirichlet allocation, " the Journal of machine Learning research, vol. 3, pp. 993-1022, 2003.
6. L. Hong,B. D. Davison Empirical study of topic modeling in twitter in Proceedings of the First Workshop on Social Media Analytics, ser. SOMA '10. New York, NY, USA: ACM, 2010, 80-88.
7. S. C. Deerwester, S. T. Dumais, T. K. Landauer, G. W. Furnas, and R. A. Harshman, " Indexing by latent semantic analysis," JASIS, vol. 41, no. 6, pp. 391-407, 1990.
8. X. Yan, J. Guo, S. Liu, X.-q. Cheng, and Y. Wang, " Clustering short text using ncut-weighted non-negative matrix factorization," in Proceedings of the 21st ACM International Conference on Information and Knowledge Management, ser. CIKM '12. New York, NY, USA: ACM, 2012, pp. 2259-2262.
9. X. Hu, L. Tang, and H. Liu, "Enhancing accessibility of microblogging messages using semantic knowledge, " in Proceedings of the 20th ACM International Conference on Information and Knowledge Management, ser. CIKM '11. New York, NY, USA: ACM, 2011, pp. 2465-2468.
10. D. Ramage, D. Hall, R. Nallapati, and C. D. Manning, " Labeled lda: A supervised topic model for credit attribution in multi-labeled corpora," in Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, ser. EMNLP '09. Stroudsburg, PA, USA: ACL, 2009, pp. 248-256.
11. S. Li, G. Huang, R. Tan, and R. Pan, "Tag-weighted dirichlet allocation, " in Proceedings of the 13th International Conference on Data Mining, ser. ICDM'13. Los Alamitos, CA, USA: IEEE Computer Society, 2013, pp. 438-447.
12. D. M. Blei, A. Y. Ng, and M. I. Jordan, "The author-topic model for authors and documents, " the Journal of machine Learning research, vol. 3, pp. 993-1022, 2003.
13. T. Griffiths, " Gibbs sampling in the generative model of Latent Dirichlet Allocation," Stanford University, Tech. Rep., 2002. [Online]. Available: www-psych.sta nford.edu/gruffydd/cogsci02/lda.ps
14. D. M. Romero, B. Meeder, and J. Kleinberg, " Differences in the mechanics of information diffusion across topics: Idioms, political hashtags, and complex contagion on twitter," in Proceedings of the 20th International Conference on World Wide Web, ser. WWW '11. New York, NY, USA: ACM, 2011, pp. 695-704.