Perceptions of Secondhand E-cigarette Aerosol among Twitter Users

Unger, Jennifer B.; Escobedo, Patricia; Allem, Jon-Patrick; Soto, Daniel W.; Chu, Kar-Hai; Cruz, Tess Boley

doi:10.18001/trs.2.2.5

Cited by 23 publications

(19 citation statements)

References 20 publications

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“…Social media users tend to include multiple hashtags within their posts, which resulted in duplicate tweets being collected. Duplicate tweets within keyword corpora for each year and across keyword corpora from the co-use of hashtags were removed, resulting in the inclusion of only unique tweets [ 31 ]. Data were assigned a number in ascending order and 100 tweets from each keyword corpus for each year were randomly selected for analysis, using an online random sequence generator [ 32 ].…”

Section: Methodsmentioning

confidence: 99%

E-Cigarette Advocates on Twitter: Content Analysis of Vaping-Related Tweets

McCausland

Maycock

Leaver

et al. 2020

JMIR Public Health Surveill

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Background As the majority of Twitter content is publicly available, the platform has become a rich data source for public health surveillance, providing insights into emergent phenomena, such as vaping. Although there is a growing body of literature that has examined the content of vaping-related tweets, less is known about the people who generate and disseminate these messages and the role of e-cigarette advocates in the promotion of these devices. Objective This study aimed to identify key conversation trends and patterns over time, and discern the core voices, message frames, and sentiment surrounding e-cigarette discussions on Twitter. Methods A random sample of data were collected from Australian Twitter users who referenced at least one of 15 identified e-cigarette related keywords during 2012, 2014, 2016, or 2018. Data collection was facilitated by TrISMA (Tracking Infrastructure for Social Media Analysis) and analyzed by content analysis. Results A sample of 4432 vaping-related tweets posted and retweeted by Australian users was analyzed. Positive sentiment (3754/4432, 84.70%) dominated the discourse surrounding e-cigarettes, and vape retailers and manufacturers (1161/4432, 26.20%), the general public (1079/4432, 24.35%), and e-cigarette advocates (1038/4432, 23.42%) were the most prominent posters. Several tactics were used by e-cigarette advocates to communicate their beliefs, including attempts to frame e-cigarettes as safer than traditional cigarettes, imply that federal government agencies lack sufficient competence or evidence for the policies they endorse about vaping, and denounce as propaganda “gateway” claims of youth progressing from e-cigarettes to combustible tobacco. Some of the most common themes presented in tweets were advertising or promoting e-cigarette products (2040/4432, 46.03%), promoting e-cigarette use or intent to use (970/4432, 21.89%), and discussing the potential of e-cigarettes to be used as a smoking cessation aid or tobacco alternative (716/4432, 16.16%), as well as the perceived health and safety benefits and consequences of e-cigarette use (681/4432, 15.37%). Conclusions Australian Twitter content does not reflect the country’s current regulatory approach to e-cigarettes. Rather, the conversation on Twitter generally encourages e-cigarette use, promotes vaping as a socially acceptable practice, discredits scientific evidence of health risks, and rallies around the idea that e-cigarettes should largely be outside the bounds of health policy. The one-sided nature of the discussion is concerning, as is the lack of disclosure and transparency, especially among vaping enthusiasts who dominate the majority of e-cigarette discussions on Twitter, where it is unclear if comments are endorsed, sanctioned, or even supported by the industry.

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Section: Methodsmentioning

confidence: 99%

E-Cigarette Advocates on Twitter: Content Analysis of Vaping-Related Tweets

McCausland

Maycock

Leaver

et al. 2020

JMIR Public Health Surveill

View full text Add to dashboard Cite

show abstract

“…First, the definition of a health-promoting message was a message that included both health behaviors and health outcomes [ 15 ], so we excluded some messages, such as messages only referring to the cause of a disease. Second, in a health topic, the amount of social content was often much larger than the amount of health professional content [ 61 ]. Third, we found that the celebrity effect exists in Weibo health themes.…”

Section: Discussionmentioning

confidence: 99%

Factors Associated With Influential Health-Promoting Messages on Social Media: Content Analysis of Sina Weibo

Rao¹,

Zhang²,

Lv³

et al. 2020

JMIR Med Inform

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Background Social media is a powerful tool for the dissemination of health messages. However, few studies have focused on the factors that improve the influence of health messages on social media. Objective To explore the influence of goal-framing effects, information organizing, and the use of pictures or videos in health-promoting messages, we conducted a case study of Sina Weibo, a popular social media platform in China. Methods Literature review and expert discussion were used to determine the health themes of childhood obesity, smoking, and cancer. Web crawler technology was employed to capture data on health-promoting messages. We used the number of retweets, comments, and likes to evaluate the influence of a message. Statistical analysis was then conducted after manual coding. Specifically, binary logistic regression was used for the data analyses. Results We crawled 20,799 Sina Weibo messages and selected 389 health-promoting messages for this study. Results indicated that the use of gain-framed messages could improve the influence of messages regarding childhood obesity (P<.001), smoking (P=.03), and cancer (P<.001). Statistical expressions could improve the influence of messages about childhood obesity (P=.02), smoking (P=.002), and cancer (P<.001). However, the use of videos significantly improved the influence of health-promoting messages only for the smoking-related messages (P=.009). Conclusions The findings suggested that gain-framed messages and statistical expressions can be successful strategies to improve the influence of messages. Moreover, appropriate pictures and videos should be added as much as possible when generating health-promoting messages.

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“…Social media research on e-cigarettes has focused on using data from Twitter, with recent studies examining perception, 9 awareness 3031 and advertising. 1014 While sites such as Twitter were created before the ubiquitous use of smartphones, Instagram originated as a smartphone app, with features that rely on mobile devices that can take high-quality photos and have fast internet connections; when combined with vaping activities (eg, cloud chasing) that are best suited for real-time capture and sharing, it makes Instagram an ideal platform for e-cigarette users and provides ample data for researchers to explore.…”

Section: Discussionmentioning

confidence: 99%

“…910 However, Instagram—a social networking site focused on picture-based content—has been underused for these purposes. 11 Instagram allows users to capture and customise photos to share online.…”

Section: Introductionmentioning

confidence: 99%

Vaping on Instagram: cloud chasing, hand checks and product placement

et al. 2016

Self Cite

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Introduction This study documented images posted on Instagram of electronic cigarettes (e-cigarette) and vaping (activity associated with e-cigarette use). Although e-cigarettes have been studied on Twitter, few studies have focused on Instagram, despite having 500 million users. Instagram’s emphasis on images warranted investigation of e-cigarettes, as past tobacco industry strategies demonstrated that images could be used to mislead in advertisements, or normalise tobacco-related behaviours. Findings should prove informative to tobacco control policies in the future. Methods 3 months of publicly available data were collected from Instagram, including images and associated metadata (n=2208). Themes of images were classified as (1) activity, for example, a person blowing vapour; (2) product, for example, a personal photo of an e-cigarette device; (3) advertisement; (4) text, for example, ‘meme’ or image containing mostly text and (5) other. User endorsement (likes) of each type of image was recorded. Caption text was analysed to explore different trends in vaping and e-cigarette-related text. Results Analyses found that advertisement-themed images were most common (29%), followed by product (28%), and activity (18%). Likes were more likely to accompany activity and product-themed images compared with advertisement or text-themed images (p<0.01). Vaping-related text greatly outnumbered e-cigarette-related text in the image captions. Conclusions Instagram affords its users the ability to post images of e-cigarette-related behaviours and gives advertisers the opportunity to display their product. Future research should incorporate novel data streams to improve public health surveillance, survey development and educational campaigns.

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Perceptions of Secondhand E-cigarette Aerosol among Twitter Users

Cited by 23 publications

References 20 publications

E-Cigarette Advocates on Twitter: Content Analysis of Vaping-Related Tweets

E-Cigarette Advocates on Twitter: Content Analysis of Vaping-Related Tweets

Factors Associated With Influential Health-Promoting Messages on Social Media: Content Analysis of Sina Weibo

Vaping on Instagram: cloud chasing, hand checks and product placement

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