Information credibility on twitter in emergency situation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7299 LNCS, Issue , 2012, Pages 45-59

  Xia, Xin ^a   Yang, Xiaohu ^a   Wu, Chao ^a   Li, Shanping ^a   Bao, Linfeng ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Bayesian Network; emergency situation; information credibility; Sequential K means; Twitter

Indexed keywords

DATA SETS; EMERGENCY SITUATION; INFORMATION CREDIBILITY; INFORMATION DIFFUSION; K-MEANS; LEARNING BAYESIAN NETWORKS; MONITOR MODELS; PUBLIC OPINIONS; SOCIAL BEHAVIOR; TRAINING DATASET; TWITTER;

BAYESIAN NETWORKS; BEHAVIORAL RESEARCH; INFORMATION SCIENCE; LEARNING ALGORITHMS;

SOCIAL NETWORKING (ONLINE);

EID: 84862190670     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-30428-6_4     Document Type: Conference Paper

References (21)

1. Boyd, D., Golder, S., Lotan, G.: Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. In: HICSS-43, pp. 1-10. IEEE, Kauai (2010)
2. Vieweg, S.: Microblogged contributions to the emergency arena: Discovery, interpretation and implications. Computer Supported Collaborative Work (2010)
3. Flanagin, A.J., Metzger, M.J.: Perceptions of Internet information credibility. Journalism and Mass Communication Quarterly 77, 515-540 (2000)
4. Juffinger, A., Granitzer, M., Lex, E.: Blog credibility ranking by exploiting verified content. In: WICOW, Madrid, Spain, pp. 51-58 (2009)
5. Johnson, T.J., Kaye, B.K., Bichard, S.L., Wong, W.J.: Every Blog Has Its Day: Politically-interested Internet Users' Perceptions of Blog Credibility. Journal of Computer-Mediated Communication 13, 100-122 (2008)
6. Benevenuto, F., Magno, G., Rodrigues, T., Almeida, V.: Detecting spammers on twitter. In: Seventh Annual Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference, Redmond, Washington, US (2010)
7. Jindal, N., Liu, B.: Opinion spam and analysis. In: WSDM 2008, Palo Alto, California, USA, pp. 219-230 (2008)
8. Stringhini, G., Kruegel, C., Vigna, G.: Detecting spammers on social networks. In: ACSAC 2010, Austin, Texas, USA, pp. 1-9 (2010)
9. Castillo, C., Mendoza, M., Poblete, B.: Information credibility on twitter. In: WWW 2011, Hyderabad, India, pp. 675-684 (2011)
10. Mathioudakis, M., Koudas, N.: TwitterMonitor: trend detection over the twitter stream. In: Proceedings of the 2010 International Conference on Management of Data, pp. 1155-1158 (2010)
11. Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes Twitter users: real-time event detection by social sensors. In: WWW 2010, Raleigh, North Carolina, pp. 851-860 (2010)
12. Hughes, A.L., Palen, L.: Twitter adoption and use in mass convergence and emergency events. International Journal of Emergency Management 6, 248-260 (2009)
13. Mendoza, M., Poblete, B., Castillo, C.: Twitter Under Crisis: Can we trust what we RT? In: 1st Workshop on Social Media Analytics (SOMA 2010), Washington, DC, USA, pp. 71-79 (2010)
14. MacQueen, J.: Some methods for classification and analysis of multivariate observations. Presented at the Proceedings of the Fifth Berkeley Symposium (1967)
15. Burges, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery 2, 121-167 (1998)
16. Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G.J., Ng, A., Liu, B., Yu, P.S.: Top 10 algorithms in data mining. Knowledge and Information Systems 14, 1-37 (2008)
17. Koller, D., Friedman, N.: Probabilistic graphical models. MIT Press (2009)
18. Cooper, G.F., Herskovits, E.: A Bayesian method for the induction of probabilistic networks from data. Machine Learning 9, 309-347 (1992)
19. Buntine, W.: A guide to the literature on learning probabilistic networks from data. IEEE Transactions on Knowledge and Data Engineering 8, 195-210 (1996)
20. Friedman, N., Geiger, D., Goldszmidt, M.: Bayesian network classifiers. Machine Learning 29, 131-163 (1997)
21. Bouckaert, R.R., Frank, E., Hall, M.A., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: WEKA"Cexperiences with a java opensource project. Journal of Machine Learning Research 11, 2533-2541 (2010)