Tracking the Human Papillomavirus Vaccine Risk Misinformation: An Explorative Study to Examine How the Misinformation Has Spread in User-Generated Content. Issue 1 (September 2020)

• Record Type: Journal Article
• Authors: Chin, Jessie; Chin, Chieh-Li; Panday, Sakshi; Ghazanfari, Anoosheh; Jagadeesan, Ganesh; Wang, Ziyi; Ontengco, Ana; Chang, Amy; Liu, Bing; Schwartz, Alan; Caskey, Rachel
• Is Part Of: Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. Volume 9:Issue 1(2020)
• Page Start: 312
• Page End: 316
• Publication Date: 2020-09
• Subjects: Human engineering -- Periodicals; Medical care -- Periodicals; 620.8
• DOI: 10.1177/2327857920091069
• Languages: English
• ISSNs: 2327-8579

Abstract

The goal of the study is to identify and track the dissemination patterns of true and false information about Human Papillomavirus (HPV) vaccines on twitter from 2013 to 2017. We applied a patient-driven HPV-vaccine risk lexicon combining with natural language processing (NLP) models and network analyses to explore the spread of verified true and false HPV-vaccine information. The explorative analyses showed different dissemination patterns of the most popular verified true and false messages about HPV vaccines, which false messages went viral than the true messages. Implications on detecting false HPV-vaccine related information were also discussed.