Characterizing JUUL-related posts on Twitter

Abstract

Background: As vaping rapidly becomes more prevalent, social media data can be harnessed to capture individuals' discussions of e-cigarette products quickly. The JUUL vaporizer is the latest advancement in e-cigarette technology, which delivers nicotine to the user from a device that is the size and shape of a thumb drive. Despite JUUL's growing popularity, little research has been conducted on JUUL. Here we utilized Twitter data to determine the public's early experiences with JUUL describing topics of posts.

Methods: Twitter posts containing the term "JUUL" were obtained for 1 April 2107 to 14 December 2017. Text classifiers were used to identify topics in posts (n = 81,689).

Results: The most prevalent topic wasPerson Tagging (use of @username to tag someone in a post) at 20.48% followed by Pods (mentions of JUUL's refill cartridge) at 14.72% and Buying (mentions of purchases) at 10.49%. The topic School (posts indicative of using JUUL or seeing someone use JUUL while at elementary, middle, or high school) comprised 3.66% of posts. The topic of Quit Smoking was rare at 0.29%.

Conclusions: Data from social media may be used to extend the surveillance of newly introduced vaping products. Findings suggest Twitter users are bonding around, and inquiring about, JUUL on social media. JUUL's discreetness may facilitate its use in places where vaping is prohibited. Educators may be in need of training on how to identify JUUL in the classroom. Despite JUUL's branding as a smoking alternative, very few Twitter users mentioned smoking cessation with JUUL.

Keywords: Electronic cigarettes; JUUL; Social media; Twitter; Vaping.

Fig. 1.

Prevalence of Topics. Note: The bold diagonal line indicates the prevalence of the 11 topics identified. The off-diagonal lines indicate topic overlap. For example, a hypothetical post such “I lost my JUUL at recess” could be classified under Lost & Found and School. The number of posts containing both content would be found at the intersection of the matrix for these two topics or 0.03%.

Fig. 2.

Prevalence of Topics within Person Tagging. Note: The bold diagonal line indicates the prevalence of the 13 topics identified in the subset of tweets for the Person Tagging topic. The off-diagonal lines indicate topic overlap.

Fig. 3.

Prevalence of Topics within School. Note: The bold diagonal line indicates the prevalence of the 10 topics identified in the subset of tweets for the School topic. The off-diagonal lines indicate topic overlap.