Event detection for exploring emotional upheavals of depressive people

Pin Hua Wu, Jia-Ling Koh, Arbee L.P. Chen

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

Abstract

Depression is a common illness that negatively affects how people feel, think, and act. It causes feelings of sadness and sleeping disorders. In serious cases, it leads to self-harm or suicide. Many researchers in computer science addressed the problem of depression detection. However, less research concerns the emotional upheaval of depressive people and investigates the reasons behind the depression. In this paper, a deep learning model is first constructed to automatically determine the negative sentiment degree for a Facebook post. The curves of emotional upheavals for depressive users are then generated. Based on the post contents, weather, and news data, relevant events are detected to infer the reasons of the negative emotions. A correlation analysis between the behavioral data of the depressive users on Facebook and their negative emotions is also conducted. The results of this study can not only provide a self-examination tool for depressive people, but also serve as a diagnostic assessment reference for medical personnel.

Original languageEnglish
Title of host publicationProceedings of the ACM Symposium on Applied Computing
PublisherAssociation for Computing Machinery
Pages2086-2095
Number of pages10
ISBN (Print)9781450359337
DOIs
Publication statusPublished - 2019 Jan 1
Event34th Annual ACM Symposium on Applied Computing, SAC 2019 - Limassol, Cyprus
Duration: 2019 Apr 82019 Apr 12

Publication series

NameProceedings of the ACM Symposium on Applied Computing
VolumePart F147772

Conference

Conference34th Annual ACM Symposium on Applied Computing, SAC 2019
CountryCyprus
CityLimassol
Period19/4/819/4/12

Keywords

  • Depression
  • Event detection
  • Social media
  • Text sentiment classification

ASJC Scopus subject areas

  • Software

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  • Cite this

    Wu, P. H., Koh, J-L., & Chen, A. L. P. (2019). Event detection for exploring emotional upheavals of depressive people. In Proceedings of the ACM Symposium on Applied Computing (pp. 2086-2095). (Proceedings of the ACM Symposium on Applied Computing; Vol. Part F147772). Association for Computing Machinery. https://doi.org/10.1145/3297280.3297485