Twitter catches the flu: Detecting influenza epidemics using Twitter

EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2011, Pages 1568-1576

  Aramaki, Eiji ^a   Maskawa, Sachiko ^a   Morita, Mizuki ^b  

^a UNIVERSITY OF TOKYO   (Japan)

^b NATIONAL INSTITUTE OF BIOMEDICAL INNOVATION   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

GOLD STANDARDS; SOCIAL MEDIA; STATE-OF-THE-ART METHODS;

COMPUTATIONAL LINGUISTICS; EPIDEMIOLOGY; INFORMATION USE; SOCIAL NETWORKING (ONLINE); SUPPORT VECTOR MACHINES;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 80053290412     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Barbosa, L. and J. Feng. 2010. Robust Sentiment Detection on Twitter from Biased and Noisy Data. In Proc. 23rd Intl. Conf. on Computational Linguistics (COLING).
2. Boyd, D., S. Golder, and G. Lotan. 2010. Tweet, tweet, retweet: Conversational aspects of retweeting on Twitter. In Proc. HICSS43.
3. Breiman L. Random Forests. 2001. Machine learning, 45(1): 5-32.
4. Breiman, L. Bagging predictors. 1996. Machine learning, 24(2):123-140.
5. Cortes C. and V. Vapnik. 1995. Support vector networks. In Machine Learning, pp. 273-297.
6. Chapman, W., W. Bridewell, P. Hanbury, G.F. Cooper, and B. Buchanan. 2001. A simple algorithm for identifying negated findings and diseases in discharge summaries. Journal of Biomedical Informatics, 5:301-310.
7. Chapman, W., J. Dowling, and D. Chu. 2007. Con Text: An algorithm for identifying contextual features from clinical text. Biological, translational, and clinical language processing (BioNLP2007), pp. 81-88.
8. Elkin, P.L., S.H. Brown, B.A. Bauer, C.S. Husser, W. Carruth, L.R. Bergstrom, and D.L. Wahner-Roedler. 2005. A controlled trial of automated classification of negation from clinical notes. BMC Medical Informatics and Decision Making 5:13.
9. Espino, J., W. Hogan, and M. Wagner. 2003. Telephone triage: A timely data source for surveillance of influenza-like diseases. In Proc. of Annual Symposium of AMIA, pp. 215-219.
10. Finin, T., W. Murnane, A. Karandikar, N. Keller, J. Martineau, and M. Dredze. 2010. Annotating named entities in Twitter data with crowdsourcing. In Proc. NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk (CSLDAMT '10), pp. 80-88.
11. Freund, Y. and R. Schapire. 1996. Experiments with a new boosting algorithm. In Machine Learning Intl. Workshop, pp.148-156.
12. Ginsberg, J., M.H. Mohebbi, R.S. Patel, and L. Brammer. 2009. Detecting influenza epidemics using search engine query data, Nature Vol. 457 (19).
13. Huang, Y. and H.J. Lowe. 2007. A novel hybrid approach to automated negation detection in clinical radiology reports. Journal of the American Medical Informatics Association, 14(3):304-311.
14. Huberman, B. and D. R. F. Wu. 2009. Social networks that matter: Twitter under the microscope. First Monday, Vol. 14.
15. Hulth, A., G. Rydevik, and A. Linde. 2009. Web Queries as a Source for Syndromic Surveillance. PLoS ONE 4(2).
16. Johnson, HA., MM. Wagner, WR. Hogan, W. Chapman, RT. Olszewski, J. Dowling, and G. Barnas. 2004. Analysis of Web access logs for surveillance of influenza. Stud. Health Technol. Inform. 107(Pt 2):1202-1206.
17. Magruder, S. 2003. Evaluation of over-the-counter pharmaceutical sales as a possible early warning indicator of human disease. Johns Hopkins University APL Technical Digest 24:349-353.
18. Milstein, S., A. Chowdhury, G. Hochmuth, B. Lorica, and R. Magoulas. 2008. Twitter and the micromessaging revolution: Communication, connections, and immediacy, 140 characters at a time. O'Reilly Media.
19. Mutalik, P.G., A. Deshpande, and P.M. Nadkarni. 2001. Use of general purpose negation detection to augment concept indexing of medical documents: A quantitative study using the UMLS. Journal of the American Medical Informatics Association, 8(6):598-609.
20. Paul, MJ. and M. Dredze. 2011. You Are What You Tweet: Analyzing Twitter for Public Health. In Proc. of the 5th International AAAI Conference on Weblogs and Social Media (ICWSM).
21. Polgreen, PM., Y. Chen, D.M. Pennock, and F.D. Nelson. 2008. Using Internet Searches for Influenza Surveillance, Clinical Infectious Diseases Vol. 47 (11) pp. 1443-1448.
22. Quinlan. J. 1993. C4. 5: programs for machine learning. Morgan Kaufmann.
23. Sakaki, T., M. Okazaki, and Y. Matsuo. 2010. Earthquake shakes Twitter users: real-time event detection by social sensors, in Proc. of Conf. on World Wide Web (WWW).