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2018 IEEE International Conference on Healthcare Informatics (ICHI) (2018)
New York City, NY, USA
Jun 4, 2018 to Jun 7, 2018
ISSN: 2575-2634
ISBN: 978-1-5386-5377-7
pp: 386-387
ABSTRACT
Social media such as Twitter can provide urgently needed drug abuse intelligence to support the campaign of fighting against the national drug abuse crisis. We employed a targeted tweet collection approach and a two-staged annotation strategy that combines conventional annotation with crowdsourced annotation to produce annotated training dataset. In this demo, we share deep learning models trained in a boosting manner using the data from the two-staged annotation method and unlabeled data collection to detect drug abuse risk behavior in tweets.
INDEX TERMS
drugs, learning (artificial intelligence), social networking (online)
CITATION

H. Hu et al., "Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets," 2018 IEEE International Conference on Healthcare Informatics (ICHI), New York City, NY, USA, 2018, pp. 386-387.
doi:10.1109/ICHI.2018.00066
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