ArticleFrontiers in communication2020
#Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis.
Article in Frontiers in communication, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed.
- US adolescents' response to nicotine warning labels in influencer e-cigarette marketing social media posts: a survey-based randomised between-subject experiment.Tobacco control · 2025Trial
- Sharing Antivaping Social Media Messages.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2025Trial
- #MiniCupVape E-Cigarettes Promoted on Instagram: A Youth Participatory Action Research Approach.American journal of preventive medicine · 2026Article
- Parsing Instagram Posts for Smoking Imagery Amongst Users: A Content Analysis.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2026Article
- Generative AI in a new era of computer model-informed tobacco research: a short report.Tobacco control · 2026Article
- Evading regulation: young people's exposure to harmful commodity marketing in the social media feeds of their favourite influencers.Health promotion international · 2026Article
- Leveraging Large Language Models to Identify Engagement-Driving Features in Vaping-Related TikTok Videos: Cross-Sectional Study.Journal of medical Internet research · 2025Article
- Demographic Trends in E-Cigarette Social Media Marketing: Perceiving Gender Presentation and Facial Age Via Computer Vision.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025Article
- Generative artificial intelligence and machine learning methods to screen social media content.PeerJ. Computer science · 2025Article
- Vitamin C Protects from Impairment of Memory Induced by E-Cigarette Aerosol Exposure.Current neuropharmacology · 2025Article
- Concurrent Mentions of Vaping and Alcohol on Twitter: Latent Dirichlet Analysis.Journal of medical Internet research · 2024Article
- Social Media Marketing Strategies for Electronic Cigarettes: Content Analysis of Chinese Weibo Accounts.Journal of medical Internet research · 2024Article
- The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study.Journal of medical Internet research · 2024Article
- Scalable Surveillance of E-Cigarette Products on Instagram and TikTok Using Computer Vision.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024Article
- Vaping: Public Health, Social Media, and Toxicity.Online journal of public health informatics · 2024Article
- Social Network Analysis of e-Cigarette-Related Social Media Influencers on Twitter/X: Observational Study.JMIR formative research · 2024Article
- Using Computer Vision to Detect E-cigarette Content in TikTok Videos.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024Article
- Young Adults' Exposure to and Engagement With Tobacco-Related Social Media Content and Subsequent Tobacco Use.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024Article
- Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024Article
- Enhancing sentiment and intent analysis in public health via fine-tuned Large Language Models on tobacco and e-cigarette-related tweets.Frontiers in big data · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
E-cigarette use is increasing dramatically among adolescents as social media marketing portrays "vaping" products as healthier alternatives to conventional cigarettes. In September 2018, the Food and Drug Administration (FDA) launched an anti-vaping campaign, in U.S. high schools, on social media and other platforms, emphasizing "The Real Cost" of e-cigarettes. Using a novel deep learning approach, we assessed changes in vaping-related content on Instagram from 2017 to 2019 and drew an inference about the initial impact of the FDA's Real Cost campaign on Instagram. We collected 245,894 Instagram posts that used vaping-related hashtags (e.g., #vape, #ejuice) in four samples from 2017 to 2019. We compared the "like" count from these posts before and after the FDA campaign. We used deep learning image classification to analyze 49,655 Instagram image posts, separating images of men, women, and vaping devices. We also conducted text analysis and topic modeling to detect the common words and themes in the posted captions. Since September 2018, the FDA-sponsored hashtag #TheRealCost has been used about 50 times per month on Instagram, whereas vaping-related hashtags we tracked were used up to 10,000 times more often. Comparing the pre-intervention (2017, 2018) and post-intervention (2019) samples of vaping-related Instagram posts, we found a three-fold increase in the median "like" count (10 vs. 28) and a 6-fold increase in the proportion of posts with more than 100 likes (2 vs. 15%). Over 70% of Instagram vaping images featured e-juices and devices, with a growing number of images depicting a "pod," the type of discrete vaping device that delivers high concentration of nicotine and is favored by novice e-cigarette users. In addition, the Instagram analytics data shared by the vaping influencers we interviewed showed underage Instagram users among their followers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.