A prior knowledge based neural attention model for opioid topic identification

Riheng Yao, Qiudan Li, Wei Hsuan Lo-Ciganic, Daniel Dajun Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The opioid epidemic has become a serious public health crisis in the United States. Social media sources such as Reddit containing user-generated content may be a valuable safety surveillance platform to evaluate discussions discerning opioid use. This paper proposes a prior knowledge based neural attention model for opioid topics identification, which considers prior knowledge with attention mechanism. Experimental results on a real-world dataset show that our model can extract coherent topics, the identified less discussed but important topics provide more comprehensive information for opioid safety surveillance.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019
EditorsXiaolong Zheng, Ahmed Abbasi, Michael Chau, Alan Wang, Lina Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages215-217
Number of pages3
ISBN (Electronic)9781728125046
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019 - Shenzhen, China
Duration: Jul 1 2019Jul 3 2019

Publication series

Name2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019

Conference

Conference17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019
CountryChina
CityShenzhen
Period7/1/197/3/19

Keywords

  • Attention
  • Opioid
  • Prior knowledge
  • Topic

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Information Systems

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  • Cite this

    Yao, R., Li, Q., Lo-Ciganic, W. H., & Zeng, D. D. (2019). A prior knowledge based neural attention model for opioid topic identification. In X. Zheng, A. Abbasi, M. Chau, A. Wang, & L. Zhou (Eds.), 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019 (pp. 215-217). [8823280] (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISI.2019.8823280