IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v10y2023i1d10.1057_s41599-023-02313-6.html
   My bibliography  Save this article

Detecting depression on video logs using audiovisual features

Author

Listed:
  • Kyungeun Min

    (Sungkyunkwan University)

  • Jeewoo Yoon

    (Sungkyunkwan University)

  • Migyeong Kang

    (Sungkyunkwan University)

  • Daeun Lee

    (Sungkyunkwan University)

  • Eunil Park

    (Sungkyunkwan University
    Sungkyunkwan University)

  • Jinyoung Han

    (Sungkyunkwan University
    Sungkyunkwan University)

Abstract

Detecting depression on social media has received significant attention. Developing a depression detection model helps screen depressed individuals who may need proper treatment. While prior work mainly focused on developing depression detection models with social media posts, including text and image, little attention has been paid to how videos on social media can be used to detect depression. To this end, we propose a depression detection model that utilizes both audio and video features extracted from the vlogs (video logs) on YouTube. We first collected vlogs from YouTube and annotated them into depression and non-depression. We then analyze the statistical differences between depression and non-depression vlogs. Based on the lessons learned, we build a depression detection model that learns both audio and visual features, achieving high accuracy. We believe our model helps detect depressed individuals on social media at an early stage so that individuals who may need appropriate treatment can get help.

Suggested Citation

  • Kyungeun Min & Jeewoo Yoon & Migyeong Kang & Daeun Lee & Eunil Park & Jinyoung Han, 2023. "Detecting depression on video logs using audiovisual features," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-02313-6
    DOI: 10.1057/s41599-023-02313-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-023-02313-6
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-023-02313-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Oecd, 2023. "COVID-19 and science for policy and society," OECD Science, Technology and Industry Policy Papers 154, OECD Publishing.
    2. ., 2023. "Societal trends," Chapters, in: Institutional Theory and Organizational Change, chapter 5, pages 74-88, Edward Elgar Publishing.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      More about this item

      Statistics

      Access and download statistics

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-02313-6. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.