A machine learning language model approach to evaluating mental health awareness content across Spanish- and English-language social media posts on Twitter
Mental health awareness content on Twitter appears not to be consistently available or aligned with clinical values, disadvantaging Spanish-language social media users, possibly leading to divergent priorities concerning population mental health. Nevertheless, natural language processing techniques offers a viable method to further understand unequal mental health awareness content across various language and cultural social media.
Authors
- Melissa J. DuPont‐Reyes (ORCID: https://orcid.org/0000-0002-0284-1714)
- Wenxue Zou (ORCID: https://orcid.org/0000-0002-4151-4230)
- Jinxu Li (ORCID: https://orcid.org/0000-0001-7978-2129)
- Lu Tang (ORCID: https://orcid.org/0000-0002-1850-1511)
- Alice P. Villatoro (ORCID: https://orcid.org/0000-0002-4865-4084)
Institutions
- Santa Clara University (US)
- Coastal Carolina University (US)
- Columbia University Irving Medical Center (US)
- Conway School of Landscape Design (US)
- Columbia University (US)
- Texas A&M University (US)
Publication Details
- Journal
- Social Psychiatry and Psychiatric Epidemiology
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1007/s00127-025-02870-y
- Citations
- 3
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 7.32
Funders
- Robert Wood Johnson Foundation