Decoding HIV Discourse on Social Media: Large-Scale Analysis of 191,972 Tweets Using Machine Learning, Topic Modeling, and Temporal Analysis

HIV 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 digital platforms in health communication, ex...

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Vydané v:	Journal of medical Internet research Ročník 27; číslo 8; s. e76745
Hlavní autori:	Zhan, Xiangming, Song, Meijia, Shrader, Cho Hee, Forbes, Chad E, Algarin, Angel B
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Canada Journal of Medical Internet Research 29.08.2025 JMIR Publications
Predmet:	Analysis Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health Behavioral Surveillance for Population and Public Health Informatics COVID-19 Evidence-based medicine Health care industry HIV (Viruses) HIV Infections - psychology HIV patients HIV testing HIV/AIDS/STI Prevention and Care Humans Infodemiology and Infoveillance Infoveillance and Social Listening Machine Learning Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine Natural Language Processing Original Paper Patient compliance Public (e)Health, Digital Epidemiology and Public Health Informatics Social media Social Media - statistics & numerical data public health informatics topic modeling HIV prevention machine learning temporal analysis social media
ISSN:	1438-8871, 1439-4456, 1438-8871
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