Vaping associated with healthy food words: A content analysis of Twitter.
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ABSTRACT:
SUBMITTER: Basanez T
PROVIDER: S-EPMC6180293 | biostudies-other | 2018 Dec
REPOSITORIES: biostudies-other
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Vaping associated with healthy food words: A content analysis of Twitter.
Basáñez Tatiana T Majmundar Anuja A Cruz Tess Boley TB Unger Jennifer B JB
Addictive behaviors reports 20180924
E-cigarettes were initially introduced as a less harmful alternative to combustible cigarettes, but marketing efforts may now be exceeding these claims by associating e-cigarettes with words related to healthy foods. These associations could mislead people to assume vaping is a healthy practice. Tweets from January to March 2017 were obtained from the Twitter Streaming Application Programming Interface (API) to assess content about vaping linked to healthy food words. Tweets were classified into ...[more]
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Project description:The importance of breastfeeding for maternal and infant health is well-established, yet complex and intertwined sociocultural barriers contribute to suboptimal breastfeeding rates in most countries. Large-scale campaigns for evidence dissemination and promotion through targeted interventions on social media may help overcome some of these barriers. To date, most breastfeeding research on social media only focuses on content analysis, and there remains limited knowledge about the social networks of online communities (who interacts with whom), influencers in the breastfeeding space and the diffusion of evidence-based knowledge. This study, grounded in social network theory, aims to better understand the breastfeeding communication landscape on Twitter including determining the presence of a breastfeeding network, communities and key influencers. Further, we characterize influencer interactions, roles and the content being shared. The study revealed an overall breastfeeding social network of 3,798 unique individuals (users) and 3,972 tweets with commonly used hashtags (e.g., #breastfeeding and #normalizebreastfeeding). Around one third of users (n = 1,324, 34%) exchanged pornographic content (PC) that sexualized breastfeeding. The non-PC network (n = 2,474 users) formed 144 unique communities, and content flowing within the network was disproportionately influenced by 59 key influencers. However, these influencers had mostly inward-oriented interaction (% composition, E-I index: 47% professionals, -0.18; 41% interested citizens, -0.67; 12% companies, -0.18), limiting opportunities for evidence-based dissemination to the lay public. Although more tweets about peer-reviewed research findings were sent compared with tweets about nonevidence-based lay recommendations, our findings suggest that it is the lay public who often communicated findings, which may be overcome through a targeted social network-based intervention.
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