Detecting Mental Health Illness Using Short Comments

Takahiro Baba, Kensuke Baba, Daisuke Ikeda

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)

抄録

Mental health illness has become a serious public problem. Finding changes in everyday behavior is a demand. This paper tries to detect persons who have mental health illness using their short comments posted to social network systems. The novelty of this study is using comments in a system for communication between users with mental health illness, in order to prepare a sufficient amount of supervised data for machine learning. The authors used approximately 120,000 comments in the system as positive samples and 120,000 comments in Twitter as negative samples for detecting mental health illness. Both data are posted short comments on a daily basis. The authors conducted a straightforward classification of the comments using a support vector machine and surface-level features of the comments. The accuracy of the classification is 0.92 and the characteristic phrases used for the classification are related to troubles in mental health. The ability to classify everyday statements can be expected to lead to the early detection of mental disorders.

本文言語英語
ホスト出版物のタイトルAdvanced Information Networking and Applications - Proceedings of the 33rd International Conference on Advanced Information Networking and Applications AINA-2019
編集者Makoto Takizawa, Fatos Xhafa, Leonard Barolli, Tomoya Enokido
出版社Springer Verlag
ページ265-271
ページ数7
ISBN(印刷版)9783030150310
DOI
出版ステータス出版済み - 2020
イベント33rd International Conference on Advanced Information Networking and Applications, AINA-2019 - Matsue, 日本
継続期間: 3 27 20193 29 2019

出版物シリーズ

名前Advances in Intelligent Systems and Computing
926
ISSN(印刷版)2194-5357

会議

会議33rd International Conference on Advanced Information Networking and Applications, AINA-2019
国/地域日本
CityMatsue
Period3/27/193/29/19

All Science Journal Classification (ASJC) codes

  • 制御およびシステム工学
  • コンピュータ サイエンス(全般)

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