Accepted for/Published in: JMIR Formative Research
Date Submitted: Oct 14, 2023
Date Accepted: Mar 6, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Social Network Analysis of E-cigarette-related Social Media Influencers on Twitter: Observational Study
ABSTRACT
Background:
An electronic cigarette (e-cigarette) uses a battery to heat e-liquid to generate an aerosol for consumers to inhale. E-cigarette use (vaping) has been associated with respiratory disease, cardiovascular disease, and cognitive functions. Recently, vaping has been popular, especially among youth and young adults.
Objective:
This study aims to understand social networks of social media (Twitter) influencers related to e-cigarettes through social network analysis.
Methods:
Through the Twitter streaming application programming interface (API), we identified 3,617,766 unique Twitter accounts posting e-cigarette-related tweets from May 3rd, 2021, to June 10th, 2022. From them, we identified 33 e-cigarette influencers. Furthermore, we identified and grouped the followers of these influencers into e-cigarette followers and non-e-cigarette followers. We randomly sampled 100 user accounts from e-cigarette followers and non-e-cigarette followers, respectively, and created corresponding social networks for each e-cigarette influencer. We compared different network measures (such as the clustering coefficient) between e-cigarette follower networks and non-e-cigarette follower networks.
Results:
For the identified 33 influencers, their e-cigarette follower networks have significantly higher clustering coefficients than their non-e-cigarette follower networks, 0.398 vs 0.098 (P<.001). The number of followers of e-cigarette followers is significantly higher than that of non-e-cigarette followers (322 vs. 201), with a P<.001. The number of tweets posted by e-cigarette follower networks is significantly higher (93 vs. 43, P<.001) than that by non-e-cigarette follower networks. Two major topics discussed in e-cigarette follower networks include promoting e-cigarette products or vaping activity and vaping helping with smoking cessation and harm reduction.
Conclusions:
Our study showed that e-cigarette followers of e-cigarette influencers are more closely connected than non-e-cigarette followers, providing a potentially practical intervention approach for future anti-vaping campaigns.
Citation
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Copyright
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