On-line trend analysis with topic models: Twitter trends detection topic model online

24th International Conference on Computational Linguistics - Proceedings of COLING 2012: Technical Papers

Volumn , Issue , 2012, Pages 1519-1534

  Lau, JeyHan ^a,b   Collier, Nigel ^c   Baldwin, Timothy ^a,b  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b CSIRO   (Australia)

^c NATIONAL INSTITUTE OF INFORMATICS   (Japan)

Author keywords

Online processing; Topic evolution; Topic model; Trend detection; Twitter

Indexed keywords

ONLINE PROCESSING; TOPIC EVOLUTION; TOPIC MODEL; TREND DETECTION; TWITTER;

COMPUTATIONAL LINGUISTICS;

SOCIAL NETWORKING (ONLINE);

EID: 84876797765     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Allan, J. (2002). Introduction to topic detection and tracking. In Allan, J., editor, Topic Detection and Tracking: Event-based Information Organization, pages 1-16. Kluwer.
2. AlSumait, L., Barbará, D., and Domeniconi, C. (2008). On-line LDA: Adaptive topic models for mining text streams with applications to topic detection and tracking. In Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (ICDM-08), pages 3-12, Washington, DC, USA.
3. Blei, D., Ng, A., and Jordan, M. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3:993-1022.
4. Culotta, A. (2010). Towards detecting influenza epidemics by analyzing Twitter messages. In Proceedings of the First Workshop on Social Media Analytics, pages 115-122, New York, NY, USA.
5. De Longueville, B., Smith, R., and Luraschi, G. (2009). "omg, from here, i can see the flames!": A use case of mining location based social networks to acquire spatio-temporal data on forest fires. In Proceedings of the 2009 International Workshop on Location Based Social Networks, pages 73-80, Seattle, Washington.
6. Diao, Q., Jiang, J., Zhu, F., and Lim, E. (2012). Finding bursty topics from microblogs. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL HLT 2012), pages 536-544, Jeju Island, Korea.
7. Griffiths, T. and Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101:5228-5235.
8. Hoffman, M., Blei, D. M., and Bach, F. (2010). Online learning for latent dirichlet allocation. In Advances in Neural Information Processing Systems 23 (NIPS-10), pages 856-864.
9. Kireyev, K., Palen, L., and Anderson, K. (2009). Applications of topics models to analysis of disaster-related Twitter data. In NIPS Workshop on Applications for Topic Models: Text and Beyond, Whistler, Canada.
10. Lampos, V. and Cristianini, N. (2010). Tracking the flu pandemic by monitoring the social web. In 2nd IAPR Workshop on Cognitive Information Processing (CIP 2010), pages 411-416, Montreal, Quebec.
11. Mathioudakis, M. and Koudas, N. (2010). TwitterMonitor: Trend detection over the Twitter stream. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, pages 1155-1158, New York, NY, USA.
12. Mimno, D., Wallach, H., Talley, E., Leenders, M., and McCallum, A. (2011). Optimizing semantic coherence in topic models. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011), pages 262-272, Edinburgh, UK.
13. Minnen, G., Carroll, J., and Pearce, D. (2001). Applied morphological processing of English. Journal of Natural Language Processing, 7(3):207-223.
14. Newman, D., Lau, J., Grieser, K., and Baldwin, T. (2010). Automatic evaluation of topic coherence. In Proceedings of Human Language Technologies: The 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL HLT 2010), pages 100-108, Los Angeles, USA.
15. Osborne, M., Petrovíc, S., McCreadie, R., Macdonald, C., and Ounis, I. (2012). Bieber no more: First story detection using twitter and wikipedia. In SIGIR 2012 Workshop on Time-aware Information Access, Oregon, USA.
16. Petrovíc, S., Osborne, M., and Lavrenko, V. (2010). Streaming first story detection with application to twitter. In Proceedings of Human Language Technologies: The 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL HLT 2010), pages 181-189, Los Angeles, USA.
17. Sakaki, T., Okazaki, M., and Matsuo, Y. (2010). Earthquake shakes Twitter users: Real-time event detection by social sensors. In Proceedings of the 19th international conference on World wide web (WWW-2010), pages 851-860, New York, NY, USA.
18. Signorini, A., Segre, A., and Polgreen, P. (2011). The use of twitter to track levels of disease activity and public concern in the u.s. during the influenza a h1n1 pandemic. PLoS ONE, 6:e19467.
19. Weng, J. and Lee, B. (2011). Event detection in Twitter. In Proceedings of the Fifth International Conference on Weblogs and Social Media (ICWSM-2011), Barcelona, Catalonia, Spain.
20. Zanzotto, F., Pennacchiotti, M., and Tsioutsiouliklis, K. (2011). Linguistic redundancy in twitter. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011), pages 659-669, Edinburgh, United Kingdom.
21. Zhao, X., Shu, B., Jiang, J., Song, Y., Yan, H., and Li, X. (2012). Identifying event-related bursts via social media activities. In Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing (EMNLP 2012), pages 1466-1477, Jeju Island, Korea.