Topics and Sentiment Surrounding Vaping on Twitter and Reddit During the 2019 EVALI Outbreak: A Comparative Study (Preprint)
Authors: Wu Dezhi , Kasson Erin , Singh Avineet , Ren Yang , Kaiser Nina , Huang Ming , Cavazos-Rehg Patricia 
Published: May 2022

BACKGROUND

Vaping or e-cigarette use has become dramatically more popular in the United States in recent years. Vaping and e-cigarette 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 as space for personal coping and empowerment.

OBJECTIVE

The current paper aims to compare vaping-related content on two popular social media platforms (i.e., Twitter with brief information and Reddit with longer opinion posts) 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.

METHODS

Data were extracted from both Twitter and Reddit from July 2019 to September 2019 at the peak of the EVALI crisis. High-throughput computational analysis (sentiment analysis and topic analysis) were conducted. In addition, in-depth manual content analyses were performed and compared to computational analysis of content on both platforms.

RESULTS

Vaping-related posts and unique users on Twitter and Reddit increased from July to September 2019, with the average post per user increasing from 1.73 to 1.98 on Twitter and 1.25 to 1.56 on Reddit. Computational analyses found the number of positive sentiment posts to be higher than negative ones on both Twitter and Reddit, while content analysis results differed indicating that negative sentiment posts were higher on Twitter based on in-depth manual review. Keywords related to age were more commonly found on Twitter based on computational analysis, while mentions of youth/young adults specifically were higher on Reddit based on clinical content analysis. Further, topics prevalent on both platforms by keywords and based on manual post reviews included marketing/regulation, marijuana/THC, and interest in quitting.

CONCLUSIONS

Post content and trending topics overlapped on both Twitter and Reddit during the EVALI period in 2019. However crucial differences in user type and content keywords were also found including more frequent mentions of health-related keywords on Twitter and more positive health outcomes from vaping mentioned on Reddit. Utilization of both computational and clinical content analysis are critical to not only identify signals of public health trends among vaping-related social media content but also to provide context on individual-level vaping risks and behaviors. By leveraging the strengths of both Twitter and Reddit as publicly available data sources, this research may provide technical and clinical insights to inform automatic detection of social media users who are vaping and may benefit from digital intervention and proactive outreach strategies on these platforms.

CLINICALTRIAL

N/A