Decoding HIV Discourse on Social Media: Large-Scale Analysis of 191,972 Tweets Using Machine Learning, Topic Modeling, and Temporal Analysis
Abstract BackgroundHIV remains a global challenge, with stigma, financial constraints, and psychosocial barriers preventing people living with HIV from accessing health care services, driving them to seek information and support on social media. Despite the growing role of dig...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
JMIR Publications
2025-08-01
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| Serie: | Journal of Medical Internet Research |
| Accesso online: | https://www.jmir.org/2025/1/e76745 |
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