Whom should I follow? Identifying relevant users during crises

HT 2013 - Proceedings of the 24th ACM Conference on Hypertext and Social Media

Volumn , Issue , 2013, Pages 139-147

  Kumar, Shamanth ^a   Morstatter, Fred ^a   Zafarani, Reza ^a   Liu, Huan ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

Author keywords

Crisis monitoring; Microblogging; Twitter; User identification; User relevance measurement

Indexed keywords

INFORMATION ACCESS; MICROBLOGGING; RELIEF EFFORTS; SOCIAL MEDIA; STATE-OF-THE-ART TECHNIQUES; TWITTER; TWO-DIMENSION; USER IDENTIFICATION;

HYPERTEXT SYSTEMS;

SOCIAL NETWORKING (ONLINE);

EID: 84879770882     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2481492.2481507     Document Type: Conference Paper

References (19)

1. G. Barbier, R. Zafarani, H. Gao, G. Fung, and H. Liu. Maximizing benefits from crowdsourced data. Computational & Mathematical Organization Theory, pages 1-23, 2012.
2. D. Blei, A. Ng, and M. Jordan. Latent dirichlet allocation. JMLR, 3: 993-1022, 2003.
3. M. Cataldi, L. Di Caro, and C. Schifanella. Emerging topic detection on twitter based on temporal and social terms evaluation. In Proceedings of the Tenth Int. Workshop on Multimedia Data Mining, page 4, 2010.
4. T. Cover, J. Thomas, et al. Elements of information theory. Wiley Online Library, 1991.
5. D. Endres and J. Schindelin. A new metric for probability distributions. Information Theory, IEEE Transactions on, 49(7): 1858-1860, 2003.
6. H. Gao, G. Barbier, and R. Goolsby. Harnessing the crowdsourcing power of social media for disaster relief. Intelligent Systems, IEEE, 26(3): 10-14, 2011.
7. L. Hong and B. Davison. Empirical study of topic modeling in twitter. In Proceedings of the First Workshop on Social Media Analytics, pages 80-88. ACM, 2010.
8. K. Kireyev, L. Palen, and K. Anderson. Applications of topics models to analysis of disaster-related twitter data. In NIPS Workshop on Applications for Topic Models: Text and Beyond, 2009.
9. S. Kumar, G. Barbier, M. A. Abbasi, and H. Liu. TweetTracker: An Analysis Tool for Humanitarian and Disaster Relief. In ICWSM. The AAAI Press, 2011.
10. L. S. Larkey and M. E. Connell. Arabic information retrieval at umass in trec-10. Technical Report ADA456273, University of Massachussetts, 2006.
11. J. Lin. Divergence measures based on the shannon entropy. Information Theory, IEEE Transactions on, 37(1): 145-151, 1991.
12. M. Mathioudakis and N. Koudas. Twittermonitor: trend detection over the twitter stream. In SIGMOD, pages 1155-1158. ACM, 2010.
13. M. Mendoza, B. Poblete, and C. Castillo. Twitter under crisis: Can we trust what we rt? In Proceedings of the First Workshop on Social Media Analytics, 2010.
14. A. Popescu and M. Pennacchiotti. Detecting controversial events from twitter. In CIKM, pages 1873-1876, 2010.
15. Y. Qu, C. Huang, P. Zhang, and J. Zhang. Microblogging after a major disaster in china: a case study of the 2010 yushu earthquake. In CSCW, pages 25-34, 2011.
16. D. Ramage, S. Dumais, and D. Liebling. Characterizing microblogs with topic models. In ICWSM, 2010.
17. T. Sakaki, M. Okazaki, and Y. Matsuo. Earthquake shakes twitter users: real-time event detection by social sensors. In Proceedings of the 19th international conference on World wide web, pages 851-860, 2010.
18. J. Tenenbaum, V. De Silva, and J. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500): 2319-2323.
19. W. Zhao, J. Jiang, J. Weng, J. He, E. Lim, H. Yan, and X. Li. Comparing twitter and traditional media using topic models. Advances in IR, pages 338-349, 2011.