Learning the relationships between drug, symptom, and medical condition mentions in social media

Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016

Volumn , Issue , 2016, Pages 739-742

  Yates, Andrew ^a   Goharian, Nazli ^a   Frieder, Ophir ^a  

^a GEORGETOWN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROBABILITY DISTRIBUTIONS;

DRUG SIDE EFFECTS; MEDICAL CONDITIONS; SOCIAL MEDIA;

SOCIAL NETWORKING (ONLINE);

EID: 84979521029     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

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2. Chen, L.; Hossain, K. S. M. T.; Butler, P.; Ramakrishnan, N.; and Prakash, B. A. 2014. Flu gone viral: Syndromic surveillance of flu on twitter using temporal topic models. In Proceedings of the 2014 IEEE International Conference on Data Mining, ICDM '14.
3. Kuhn, M.; Letunic, I.; Jensen, L. J.; and Bork, P. 2016. The sider database of drugs and side effects. Nucleic Acids Res 44(Database issue):D1075-D1079.
4. Paul, M., and Dredze, M. 2011. You are what you tweet: Analyzing twitter for public health. In International AAAI Conference on Web and Social Media.
5. Yates, A., and Goharian, N. 2013. ADRTrace: Detecting Expected and Unexpected Adverse Drug Reactions from User Reviews on Social Media Sites. In Proceedings of the 35th European conference on Advances in Information Retrieval.
6. Yates, A.; Goharian, N.; and Frieder, O. 2015. Extracting Adverse Drug Reactions from Social Media. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'15).