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Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study

BACKGROUND: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years fueled, in part, by marketing and word-of-mouth communications via social media platforms, such as Twitter. OBJECTIVE: This study examines...

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Autores principales: Kim, Annice E, Hopper, Timothy, Simpson, Sean, Nonnemaker, James, Lieberman, Alicea J, Hansen, Heather, Guillory, Jamie, Porter, Lauren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4642798/
https://www.ncbi.nlm.nih.gov/pubmed/26545927
http://dx.doi.org/10.2196/jmir.4466
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author Kim, Annice E
Hopper, Timothy
Simpson, Sean
Nonnemaker, James
Lieberman, Alicea J
Hansen, Heather
Guillory, Jamie
Porter, Lauren
author_facet Kim, Annice E
Hopper, Timothy
Simpson, Sean
Nonnemaker, James
Lieberman, Alicea J
Hansen, Heather
Guillory, Jamie
Porter, Lauren
author_sort Kim, Annice E
collection PubMed
description BACKGROUND: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years fueled, in part, by marketing and word-of-mouth communications via social media platforms, such as Twitter. OBJECTIVE: This study examines Twitter posts about e-cigarettes between 2008 and 2013 to gain insights into (1) marketing trends for selling and promoting e-cigarettes and (2) locations where people use e-cigarettes. METHODS: We used keywords to gather tweets about e-cigarettes between July 1, 2008 and February 28, 2013. A randomly selected subset of tweets was manually coded as advertising (eg, marketing, advertising, sales, promotion) or nonadvertising (eg, individual users, consumers), and classification algorithms were trained to code the remaining data into these 2 categories. A combination of manual coding and natural language processing methods was used to indicate locations where people used e-cigarettes. Additional metadata were used to generate insights about users who tweeted most frequently about e-cigarettes. RESULTS: We identified approximately 1.7 million tweets about e-cigarettes between 2008 and 2013, with the majority of these tweets being advertising (93.43%, 1,559,508/1,669,123). Tweets about e-cigarettes increased more than tenfold between 2009 and 2010, suggesting a rapid increase in the popularity of e-cigarettes and marketing efforts. The Twitter handles tweeting most frequently about e-cigarettes were a mixture of e-cigarette brands, affiliate marketers, and resellers of e-cigarette products. Of the 471 e-cigarette tweets mentioning a specific place, most mentioned e-cigarette use in class (39.1%, 184/471) followed by home/room/bed (12.5%, 59/471), school (12.1%, 57/471), in public (8.7%, 41/471), the bathroom (5.7%, 27/471), and at work (4.5%, 21/471). CONCLUSIONS: Twitter is being used to promote e-cigarettes by different types of entities and the online marketplace is more diverse than offline product offerings and advertising strategies. E-cigarettes are also being used in public places, such as schools, underscoring the need for education and enforcement of policies banning e-cigarette use in public places. Twitter data can provide new insights on e-cigarettes to help inform future research, regulations, surveillance, and enforcement efforts.
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spelling pubmed-46427982016-01-12 Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study Kim, Annice E Hopper, Timothy Simpson, Sean Nonnemaker, James Lieberman, Alicea J Hansen, Heather Guillory, Jamie Porter, Lauren J Med Internet Res Original Paper BACKGROUND: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years fueled, in part, by marketing and word-of-mouth communications via social media platforms, such as Twitter. OBJECTIVE: This study examines Twitter posts about e-cigarettes between 2008 and 2013 to gain insights into (1) marketing trends for selling and promoting e-cigarettes and (2) locations where people use e-cigarettes. METHODS: We used keywords to gather tweets about e-cigarettes between July 1, 2008 and February 28, 2013. A randomly selected subset of tweets was manually coded as advertising (eg, marketing, advertising, sales, promotion) or nonadvertising (eg, individual users, consumers), and classification algorithms were trained to code the remaining data into these 2 categories. A combination of manual coding and natural language processing methods was used to indicate locations where people used e-cigarettes. Additional metadata were used to generate insights about users who tweeted most frequently about e-cigarettes. RESULTS: We identified approximately 1.7 million tweets about e-cigarettes between 2008 and 2013, with the majority of these tweets being advertising (93.43%, 1,559,508/1,669,123). Tweets about e-cigarettes increased more than tenfold between 2009 and 2010, suggesting a rapid increase in the popularity of e-cigarettes and marketing efforts. The Twitter handles tweeting most frequently about e-cigarettes were a mixture of e-cigarette brands, affiliate marketers, and resellers of e-cigarette products. Of the 471 e-cigarette tweets mentioning a specific place, most mentioned e-cigarette use in class (39.1%, 184/471) followed by home/room/bed (12.5%, 59/471), school (12.1%, 57/471), in public (8.7%, 41/471), the bathroom (5.7%, 27/471), and at work (4.5%, 21/471). CONCLUSIONS: Twitter is being used to promote e-cigarettes by different types of entities and the online marketplace is more diverse than offline product offerings and advertising strategies. E-cigarettes are also being used in public places, such as schools, underscoring the need for education and enforcement of policies banning e-cigarette use in public places. Twitter data can provide new insights on e-cigarettes to help inform future research, regulations, surveillance, and enforcement efforts. JMIR Publications Inc. 2015-11-06 /pmc/articles/PMC4642798/ /pubmed/26545927 http://dx.doi.org/10.2196/jmir.4466 Text en ©Annice E Kim, Timothy Hopper, Sean Simpson, James Nonnemaker, Alicea J Lieberman, Heather Hansen, Jamie Guillory, Lauren Porter. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.11.2015. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Kim, Annice E
Hopper, Timothy
Simpson, Sean
Nonnemaker, James
Lieberman, Alicea J
Hansen, Heather
Guillory, Jamie
Porter, Lauren
Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study
title Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study
title_full Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study
title_fullStr Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study
title_full_unstemmed Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study
title_short Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study
title_sort using twitter data to gain insights into e-cigarette marketing and locations of use: an infoveillance study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4642798/
https://www.ncbi.nlm.nih.gov/pubmed/26545927
http://dx.doi.org/10.2196/jmir.4466
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