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Stigma, Support, and Ideation About Suicide in Indonesian Twitter: A Topic Modelling Study.

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Title: Stigma, Support, and Ideation About Suicide in Indonesian Twitter: A Topic Modelling Study.
Authors: Azizy, Afrizal Hasbi1 (AUTHOR), Thontowi, Haidar Buldan1 (AUTHOR) haidar.buldan@ugm.ac.id
Source: Omega: Journal of Death & Dying. Jun2026, Vol. 93 Issue 2, p1054-1075. 22p.
Subject Terms: *Fear, *Statistical correlation, *Conversation, *Fatigue (Physiology), *Machine learning, *Theory, *Cognition, Attitudes toward death, Suicidal ideation, Research funding, Anger, Descriptive statistics, Suicide, Mathematical models, Spirituality, Pain, Social support, Data analysis software, Social stigma
Geographic Terms: Indonesia
Reviews & Products: Twitter (Web resource)
Abstract: Stigma surrounding suicide is a massive problem in Indonesia. Thus, it is important to study how conversations about suicide take place. We take a machine learning approach and study tweets with suicide keywords to understand how people converse about suicide or express suicide ideation. Tweets with suicide-related keywords were extracted from May to June 2023. 20,057 tweets were subject to topic modelling with an 11-topic solution. While most topics contain negative messages, no purely stigmatizing topics emerge, despite prior research suggesting overwhelming stigma. Various kinds of existential, emotional, and social tweets about suicide take place among Indonesian users, indicating that Indonesian Twitter users utilize the platform to express their thoughts and emotions. Notably, religious-spiritual keywords are highly prevalent, suggesting that in a highly religious society, there is a need for policy makers and awareness campaigns to frame their positive messaging within the society's religious context. [ABSTRACT FROM AUTHOR]
Copyright of Omega: Journal of Death & Dying is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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PubType: Academic Journal
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  Data: Stigma, Support, and Ideation About Suicide in Indonesian Twitter: A Topic Modelling Study.
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  Data: <searchLink fieldCode="AR" term="%22Azizy%2C+Afrizal+Hasbi%22">Azizy, Afrizal Hasbi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Thontowi%2C+Haidar+Buldan%22">Thontowi, Haidar Buldan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> haidar.buldan@ugm.ac.id</i>
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  Data: <searchLink fieldCode="JN" term="%22Omega%3A+Journal+of+Death+%26+Dying%22">Omega: Journal of Death & Dying</searchLink>. Jun2026, Vol. 93 Issue 2, p1054-1075. 22p.
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  Data: *<searchLink fieldCode="DE" term="%22Fear%22">Fear</searchLink><br />*<searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br />*<searchLink fieldCode="DE" term="%22Conversation%22">Conversation</searchLink><br />*<searchLink fieldCode="DE" term="%22Fatigue+%28Physiology%29%22">Fatigue (Physiology)</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Theory%22">Theory</searchLink><br />*<searchLink fieldCode="DE" term="%22Cognition%22">Cognition</searchLink><br /><searchLink fieldCode="DE" term="%22Attitudes+toward+death%22">Attitudes toward death</searchLink><br /><searchLink fieldCode="DE" term="%22Suicidal+ideation%22">Suicidal ideation</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Anger%22">Anger</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Suicide%22">Suicide</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Spirituality%22">Spirituality</searchLink><br /><searchLink fieldCode="DE" term="%22Pain%22">Pain</searchLink><br /><searchLink fieldCode="DE" term="%22Social+support%22">Social support</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Social+stigma%22">Social stigma</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Indonesia%22">Indonesia</searchLink>
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  Data: <searchLink fieldCode="PS" term="%22Twitter+%28Web+resource%29%22">Twitter (Web resource)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Stigma surrounding suicide is a massive problem in Indonesia. Thus, it is important to study how conversations about suicide take place. We take a machine learning approach and study tweets with suicide keywords to understand how people converse about suicide or express suicide ideation. Tweets with suicide-related keywords were extracted from May to June 2023. 20,057 tweets were subject to topic modelling with an 11-topic solution. While most topics contain negative messages, no purely stigmatizing topics emerge, despite prior research suggesting overwhelming stigma. Various kinds of existential, emotional, and social tweets about suicide take place among Indonesian users, indicating that Indonesian Twitter users utilize the platform to express their thoughts and emotions. Notably, religious-spiritual keywords are highly prevalent, suggesting that in a highly religious society, there is a need for policy makers and awareness campaigns to frame their positive messaging within the society's religious context. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Omega: Journal of Death & Dying is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=193752807
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/00302228241253972
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
        StartPage: 1054
    Subjects:
      – SubjectFull: Fear
        Type: general
      – SubjectFull: Statistical correlation
        Type: general
      – SubjectFull: Conversation
        Type: general
      – SubjectFull: Fatigue (Physiology)
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Theory
        Type: general
      – SubjectFull: Cognition
        Type: general
      – SubjectFull: Attitudes toward death
        Type: general
      – SubjectFull: Suicidal ideation
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Anger
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Suicide
        Type: general
      – SubjectFull: Mathematical models
        Type: general
      – SubjectFull: Spirituality
        Type: general
      – SubjectFull: Pain
        Type: general
      – SubjectFull: Social support
        Type: general
      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Social stigma
        Type: general
      – SubjectFull: Indonesia
        Type: general
      – SubjectFull: Twitter (Web resource)
        Type: general
    Titles:
      – TitleFull: Stigma, Support, and Ideation About Suicide in Indonesian Twitter: A Topic Modelling Study.
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            NameFull: Azizy, Afrizal Hasbi
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            NameFull: Thontowi, Haidar Buldan
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          Dates:
            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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              Value: 93
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            – TitleFull: Omega: Journal of Death & Dying
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