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Cited by 178Mental Health via WritingMental Health Treatment and AccessSentiment Analysis and Opinion Mining

Gender and Cross-Cultural Differences in Social Media Disclosures of Mental Illness

De Choudhury, Munmun, Sharma, Sanket S., Logar, Tomaz, Eekhout, Wouter, Nielsen, René Clausen·2017·Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
DOI 10.1145/2998181.2998220
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Abstract

Cultural and gender norms shape how mental illness and therapy are perceived. However, there is a paucity of adequate empirical evidence around gender and cultural dimensions of mental illness. In this paper we situate social media as a "lens" to examine these dimensions. We focus on a large dataset of individuals who self-disclose to have an underlying mental health concern on Twitter. Having identified genuine disclosures in this data via semi-supervised learning, we examine differences in their posts, as measured via linguistic attributes and topic models. Our findings reveal significant differences between the content shared by female and male users, and by users from two western and two majority world countries. Males express higher negativity and lower desire for social support, whereas majority world users demonstrate more inhibition in their expression. We discuss the implications of our work in providing insights into the relationship of gender and culture with mental health, and in the design of gender and culture-aware health interventions.

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  • Quantitative analysis into sex and cultural differences uncovered associations with mental health and social networks, showing men express higher negativity and lower desire of social support on social media compared with women.

    “quantitative analysis into sex and cultural differences uncovered associations with mental health and social networks60, showing men express higher negativity and lower desire of social support on social media compared with women.”

    From Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare (2020) · cites this paper as [60]

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Authors
De Choudhury, M., Sharma, S. S., Logar, T., Eekhout, W., & Nielsen, R. C.
Affiliations
  • Georgia Tech, Atlanta, GA, USA
  • Georgia Institute of Technology (US)
  • United Nations (US)
  • Leiden University (NL)
ORCID
Nielsen, René Clausen
Venue
Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
Publisher
ACM
Published
2017-02-25
Pages
353-369
DOI
10.1145/2998181.2998220
OpenAlex
W2588917609
Cited by
178
References
60
Citations by year
2026: 19 · 2025: 17 · 2024: 18 · 2023: 21 · 2022: 27 · 2021: 17 · 2020: 20 · 2019: 24 · 2018: 8 · 2017: 7
FWCI
26.15
Type
conference paper
Language
en
Open access
closed
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
ACM Conference on Computer Supported Cooperative Work (CSCW) (publishedVersion)
Funders
United Nations Foundation
Topics
  • Social Sciences › Psychology › Social Psychology › Mental Health via Writing
  • Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
Keywords
mental illness, social media disclosure, gender differences, cross-cultural comparison, Twitter, self-disclosure, social support, cultural norms

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