Deep learning model for classifying drug abuse risk behavior in tweets
Document Type
Conference Proceeding
Publication Date
7-24-2018
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.
Identifier
85051129449 (Scopus)
ISBN
[9781538653777]
Publication Title
Proceedings 2018 IEEE International Conference on Healthcare Informatics Ichi 2018
External Full Text Location
https://doi.org/10.1109/ICHI.2018.00066
First Page
386
Last Page
387
Recommended Citation
Hu, Han; Moturu, Pranavi; Dharan, Kannan Neten; Geller, James; Di Iorio, Sophie; and Phan, Hai, "Deep learning model for classifying drug abuse risk behavior in tweets" (2018). Faculty Publications. 8504.
https://digitalcommons.njit.edu/fac_pubs/8504
