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Recognizing depression of social media users from their records of activities

Research Project

Project/Area Number 26870076
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Multimedia database
Web informatics, Service informatics
Research InstitutionUniversity of Tsukuba

Principal Investigator

Tsugawa Sho  筑波大学, システム情報系, 助教 (40632732)

Project Period (FY) 2014-04-01 – 2016-03-31
Project Status Completed (Fiscal Year 2015)
Budget Amount *help
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Keywordsソーシャルメディア / うつ / 機械学習 / Twitter / ソーシャルウェブ / ビッグデータ / ソーシャルメディアマイニング
Outline of Final Research Achievements

In recent years, depression is one of significant problems in the world. For the effective treatment of depression, it is important to recognize depressive tendencies of individuals. This study constructed several models to estimate depressive tendency of social media users from the features obtained from user's activities. Through experiments, we showed that using the records of user's activities is effective for recognizing depression. We also showed effective features for recognizing depression of social media users, and the relation between the length of the training period for constructing the models and their estimation accuracy.

Report

(3 results)
  • 2015 Annual Research Report   Final Research Report ( PDF )
  • 2014 Research-status Report
  • Research Products

    (7 results)

All 2016 2015 2014 Other

All Journal Article (2 results) (of which Peer Reviewed: 2 results,  Acknowledgement Compliant: 2 results) Presentation (4 results) (of which Invited: 1 results) Remarks (1 results)

  • [Journal Article] Negative messages spread rapidly and widely on social media2015

    • Author(s)
      Sho Tsugawa, and Hiroyuki Ohsaki
    • Journal Title

      Proceedings of the 3rd ACM Conference on Online Social Networks

      Volume: - Pages: 151-160

    • DOI

      10.1145/2817946.2817962

    • NAID

      120007135526

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] Recognizing depression from Twitter activity2015

    • Author(s)
      Sho Tsugawa, Y. Kikuchi, F. Kishino, K. Nakajima, Y. Itoh, and H. Ohsaki
    • Journal Title

      Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2015)

      Volume: - Pages: 3187-3196

    • DOI

      10.1145/2702123.2702280

    • Related Report
      2014 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] 通信行動データを利用したコミュニティ計測に関する研究の動向2016

    • Author(s)
      津川 翔
    • Organizer
      電子情報通信学会 コミュニケーションクオリティ研究会
    • Place of Presentation
      筑波大学 (茨城)
    • Year and Date
      2016-01-21
    • Related Report
      2015 Annual Research Report
    • Invited
  • [Presentation] ソーシャルメディアにおける投稿の感情がその拡散力に与える影響2015

    • Author(s)
      津川 翔, 大崎 博之
    • Organizer
      電子情報通信学会 コミュニケーションクオリティ研究会
    • Place of Presentation
      京都工芸繊維大学 (京都)
    • Year and Date
      2015-09-01
    • Related Report
      2015 Annual Research Report
  • [Presentation] ソーシャルメディアにおける投稿の感情がその拡散力に与える影響の分析2015

    • Author(s)
      森 久幸, 津川 翔, 大崎 博之
    • Organizer
      電子情報通信学会 通信行動工学時限研専 第 8 回研究会
    • Place of Presentation
      大阪大学吹田キャンパス(大阪)
    • Year and Date
      2015-03-09
    • Related Report
      2014 Research-status Report
  • [Presentation] グラフにおけるランダム誤りに対する次数中心性のロバスト性解析2014

    • Author(s)
      津川 翔, 大崎 博之
    • Organizer
      電子情報通信学会 CQ 研究会
    • Place of Presentation
      大阪大学豊中キャンパス (大阪)
    • Year and Date
      2014-07-10 – 2014-07-11
    • Related Report
      2014 Research-status Report
  • [Remarks] ココロスコアはかったー

    • URL

      http://www.cocoroscore.com/

    • Related Report
      2014 Research-status Report

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Published: 2014-04-04   Modified: 2017-05-10  

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