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Using Twitter Data Analysis to Understand the Perceptions, Awareness, and Barriers to the Wide Use of Pre-Exposure Prophylaxis in the United States.
Erdengasileng, Arslan; Tian, Shubo; Green, Sara S; Naar, Sylvie; He, Zhe.
Affiliation
  • Erdengasileng A; Department of Statistics, Florida State University, Tallahassee, USA.
  • Tian S; Department of Statistics, Florida State University, Tallahassee, USA.
  • Green SS; Department of Behavioral Sciences and Social Medicine, Florida State University, Tallahassee, USA.
  • Naar S; Department of Behavioral Sciences and Social Medicine, Florida State University, Tallahassee, USA.
  • He Z; School of Information, Florida State University, Tallahassee, USA.
Article in En | MEDLINE | ID: mdl-36818418
ABSTRACT
User-generated social media posts such as tweets can provide insights about the public's perception, cognitive, and behavioral responses to health-related issues. Pre-Exposure Prophylaxis (PrEP) is one of the most effective ways to reduce the risk of HIV infection. However, its utilization is low in the US, especially among populations disproportionately affected by HIV such as the age group of under 24 years old. It is therefore important to understand the barriers to the wider use of PrEP in the US using social media posts. In this study, we collected tweets from Twitter about PrEP in the past 4 years to identify such barriers by first identifying tweets about personal discussions, and then performing textual analysis using word analysis, UMLS semantic type analysis, and topic modeling. We found that the public often discussed advocacy, risks/benefits, access, pricing, insurance coverage, legislation, stigma, health education, and prevention of HIV. This result is consistent with the literature and can help identify strategies for promoting the use of PrEP, especially among young adults.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Proceedings (IEEE Int Conf Bioinformatics Biomed) Year: 2022 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Proceedings (IEEE Int Conf Bioinformatics Biomed) Year: 2022 Document type: Article Affiliation country: United States