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E-liquid-related posts to Twitter in 2018: Thematic analysis
INTRODUCTION: E-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and commun...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6579902/ https://www.ncbi.nlm.nih.gov/pubmed/31431917 http://dx.doi.org/10.1016/j.abrep.2019.100196 |
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author | Allem, Jon-Patrick Majmundar, Anuja Dharmapuri, Likhit Cruz, Tess Boley Unger, Jennifer B. |
author_facet | Allem, Jon-Patrick Majmundar, Anuja Dharmapuri, Likhit Cruz, Tess Boley Unger, Jennifer B. |
author_sort | Allem, Jon-Patrick |
collection | PubMed |
description | INTRODUCTION: E-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and communicative cues associated with e-liquids. We analyzed Twitter data to characterize key topics of conversation about e-liquids to inform surveillance, and regulatory efforts. METHODS: Twitter posts containing e-liquid-related terms (“e-liquid(s),” “e-juice(s)”) were obtained from 1 January 2018 to 31 December 2018. Text classifiers were used to identify topics of the posts (n = 15,927). RESULTS: The most prevalent topic was Promotional at 29.35% followed by Flavors at 24.22%, and Person Tagging at 21.47%. Juice Composition was next most prevalent at 17.61% followed by Cannabis at 16.83%, and Nicotine Health Risks at 6.39%. Quit Smoking was rare at 0.57%. CONCLUSION: These results suggest that flavors, cannabis, health risks of nicotine, and composition warrant consideration as targets in future surveillance, public policy, and interventions addressing the use of e-liquids. Twitter provides ample opportunity to influence the normalization, and uptake, of e-cigarette-related products among non-smokers and youth, unless regulatory restrictions, and counter messaging campaigns are developed to reduce this risk. |
format | Online Article Text |
id | pubmed-6579902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-65799022019-08-20 E-liquid-related posts to Twitter in 2018: Thematic analysis Allem, Jon-Patrick Majmundar, Anuja Dharmapuri, Likhit Cruz, Tess Boley Unger, Jennifer B. Addict Behav Rep Research Paper INTRODUCTION: E-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and communicative cues associated with e-liquids. We analyzed Twitter data to characterize key topics of conversation about e-liquids to inform surveillance, and regulatory efforts. METHODS: Twitter posts containing e-liquid-related terms (“e-liquid(s),” “e-juice(s)”) were obtained from 1 January 2018 to 31 December 2018. Text classifiers were used to identify topics of the posts (n = 15,927). RESULTS: The most prevalent topic was Promotional at 29.35% followed by Flavors at 24.22%, and Person Tagging at 21.47%. Juice Composition was next most prevalent at 17.61% followed by Cannabis at 16.83%, and Nicotine Health Risks at 6.39%. Quit Smoking was rare at 0.57%. CONCLUSION: These results suggest that flavors, cannabis, health risks of nicotine, and composition warrant consideration as targets in future surveillance, public policy, and interventions addressing the use of e-liquids. Twitter provides ample opportunity to influence the normalization, and uptake, of e-cigarette-related products among non-smokers and youth, unless regulatory restrictions, and counter messaging campaigns are developed to reduce this risk. Elsevier 2019-06-07 /pmc/articles/PMC6579902/ /pubmed/31431917 http://dx.doi.org/10.1016/j.abrep.2019.100196 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Allem, Jon-Patrick Majmundar, Anuja Dharmapuri, Likhit Cruz, Tess Boley Unger, Jennifer B. E-liquid-related posts to Twitter in 2018: Thematic analysis |
title | E-liquid-related posts to Twitter in 2018: Thematic analysis |
title_full | E-liquid-related posts to Twitter in 2018: Thematic analysis |
title_fullStr | E-liquid-related posts to Twitter in 2018: Thematic analysis |
title_full_unstemmed | E-liquid-related posts to Twitter in 2018: Thematic analysis |
title_short | E-liquid-related posts to Twitter in 2018: Thematic analysis |
title_sort | e-liquid-related posts to twitter in 2018: thematic analysis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6579902/ https://www.ncbi.nlm.nih.gov/pubmed/31431917 http://dx.doi.org/10.1016/j.abrep.2019.100196 |
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