Topics and Sentiment Surrounding Vaping on Twitter and Reddit During the 2019 e-Cigarette and Vaping Use-Associated Lung Injury Outbreak: Comparative Study

• Published in: Journal of medical Internet research 2022-12, Vol.24 (12), p.e39460-e39460
• Main Authors: Wu, Dezhi, Kasson, Erin, Singh, Avineet Kumar, Ren, Yang, Kaiser, Nina, Huang, Ming, Cavazos-Rehg, Patricia A
• Format: Article
• Language: English
• Subjects: Adolescent; Analysis; Attitude; Comparative studies; Computational linguistics; Content analysis; Disease Outbreaks; Electronic cigarettes; Electronic Nicotine Delivery Systems; Empowerment; Feasibility; Health aspects; Health status; Humans; Information sources; Injuries; Intelligence; Keywords; Language processing; Lung Injury - epidemiology; Lung Injury - etiology; Machine learning; Marijuana; Marketing; Mental disorders; Mental health; Natural language interfaces; Original Paper; Public health; Sense of community; Sentiment analysis; Social Media; Social networks; Stigma; Surveillance; Topics; United States; Vaping; Vaping - adverse effects; Young adults
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/39460

Vaping or e-cigarette use has become dramatically more popular in the United States in recent years. e-Cigarette and vaping use-associated lung injury (EVALI) cases caused an increase in hospitalizations and deaths in 2019, and many instances were later linked to unregulated products. Previous literature has leveraged social media data for surveillance of health topics. Individuals are willing to share mental health experiences and other personal stories on social media platforms where they feel a sense of community, reduced stigma, and empowerment. This study aimed to compare vaping-related content on 2 popular social media platforms (ie, Twitter and Reddit) to explore the context surrounding vaping during the 2019 EVALI outbreak and to support the feasibility of using data from both social platforms to develop in-depth and intelligent vaping detection models on social media. Data were extracted from both Twitter (316,620 tweets) and Reddit (17,320 posts) from July 2019 to September 2019 at the peak of the EVALI crisis. High-throughput computational analyses (sentiment analysis and topic analysis) were conducted. In addition, in-depth manual content analyses were performed and compared with computational analyses of content on both platforms (577 tweets and 613 posts). Vaping-related posts and unique users on Twitter and Reddit increased from July 2019 to September 2019, with the average post per user increasing from 1.68 to 1.81 on Twitter and 1.19 to 1.21 on Reddit. Computational analyses found the number of positive sentiment posts to be higher on Reddit (P