Leveraging Large Language Models to Identify Engagement-Driving Features in Vaping-Related TikTok Videos: Cross-Sectional Study
TikTok video features like background settings, young adult presence, talking, and containing emojis and funny or silly content substantially enhance user engagement. These insights offer valuable guidance for designing compelling videos in vaping prevention campaigns to improve social media user engagement.
Authors
- Karen M. Wilson (ORCID: https://orcid.org/0000-0002-2703-7001)
- Lijun Song (ORCID: https://orcid.org/0000-0003-3162-2649)
- Aditya Dubey (ORCID: https://orcid.org/0000-0002-4885-0632)
- Zidian Xie (ORCID: https://orcid.org/0000-0002-5149-7710)
- Chenliang Xu (ORCID: https://orcid.org/0000-0002-2183-822X)
- Ana Paula Cupertino (ORCID: https://orcid.org/0000-0001-7594-969X)
- Dongmei Li (ORCID: https://orcid.org/0000-0001-9140-2483)
- Nanda Kishore Korrapolu
Institutions
- Rochester Institute of Technology (US)
- University of Rochester (US)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-10-15
- DOI
- https://doi.org/10.2196/76265
- Primary Topic
- Sexuality, Behavior, and Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00