2022
DOI: 10.1136/tobaccocontrol-2021-057243
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Understanding e-cigarette content and promotion on YouTube through machine learning

Abstract: IntroductionYouTube is a popular social media used by youth and has electronic cigarette (e-cigarette) content. We used machine learning to identify the content of e-cigarette videos, featured e-cigarette products, video uploaders, and marketing and sales of e-cigarette products.MethodsWe identified e-cigarette content using 18 search terms (eg, e-cig) using fictitious youth viewer profiles and predicted four models using the metadata as the input to supervised machine learning: (1) video themes, (2) featured … Show more

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Cited by 22 publications
(26 citation statements)
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References 27 publications
(27 reference statements)
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“…( 41) Further, we found a video instructing how to modify a vaping device for use while wearing a mask. Consistent with prior studies, (12,42) e-cigarette modification videos still persist, but are now related to COVID-19. Taken together, these results show that videos endorsing risky behaviors and have gained attention from YouTube users.…”
Section: Discussionsupporting
confidence: 86%
See 2 more Smart Citations
“…( 41) Further, we found a video instructing how to modify a vaping device for use while wearing a mask. Consistent with prior studies, (12,42) e-cigarette modification videos still persist, but are now related to COVID-19. Taken together, these results show that videos endorsing risky behaviors and have gained attention from YouTube users.…”
Section: Discussionsupporting
confidence: 86%
“…We adapted a codebook that had previously been used for the analysis of e-cigarette-related content on YouTube for this study ( Table 1 ). (12) The lead author viewed the videos and categorized themes (i.e., classified the major theme as it relates to e-cigarettes and COVID-19), uploader type (who posted these videos), and featured e-cigarette products (whether these videos portrayed e-cigarette products) based on prior research(3,12) and added new themes related to COVID-19. Another author reviewed and confirmed and/or modified the themes.…”
Section: Methodsmentioning
confidence: 99%
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“…For instance, Huang et al [ 18 ] analyzed 28,000 e-cigarette–related YouTube videos and found that those videos had received more than 100 million views, indicating high engagement by users [ 18 ]. Further, e-cigarettes are frequently positively portrayed on YouTube and pro–e-cigarette videos are commonly sponsored by the e-cigarette industry [ 19 ]; 85% of the e-cigarette–related videos on YouTube are sponsored by e-cigarette marketers, including e-cigarette companies or people endorsing e-cigarette companies [ 20 ]. Pro–e-cigarette videos include portrayals of e-cigarettes as safer, cleaner, and less malodorous than combustible cigarettes [ 21 ]; videos showcasing or teaching how to conduct vape tricks (ie, using e-cigarettes to blow large, thick amounts of exhaled aerosol or shapes) [ 8 ]; modification of e-cigarette devices for unintended purposes such as increasing the temperature and using other substances in it [ 19 , 22 , 23 ]; instructions on how to use e-cigarettes (eg, how to puff) [ 24 ]; product reviews [ 25 ]; and health information or misinformation about e-cigarette use [ 26 ].…”
Section: Introductionmentioning
confidence: 99%
“…For instance, males have consistently shown a higher level of e-cigarette use among adolescents and adults [ 31 ], and data suggest that e-cigarette–related videos such as vape tricks videos mostly feature young men and seem to be targeting this population [ 8 ]. A recent study identified that e-cigarette content on YouTube contained themes related to product reviews (provide reviews of e-cigarette products), instructional videos (teach viewers how to use, modify, or create e-cigarette products), health information (provide health information related to e-cigarettes), vape tricks (feature different vape tricks), cannabis (cannabis vaping–related topics), and other (a variety of other themes such as news clips related to e-cigarette use) [ 19 ]. However, less known is whether these video themes are differentially exposed to users by their demographic attributes.…”
Section: Introductionmentioning
confidence: 99%