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Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018

News media monitoring is an important scientific tool. By treating news reporters as data collectors and their reports as qualitative accounts of a fast changing public health landscape, researchers can glean many valuable insights. Yet, there have been surprisingly few innovations in public health...

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Detalles Bibliográficos
Autores principales: Ayers, John W., Dredze, Mark, Leas, Eric C., Caputi, Theodore L., Allem, Jon-Patrick, Cohen, Joanna E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6214510/
https://www.ncbi.nlm.nih.gov/pubmed/30388126
http://dx.doi.org/10.1371/journal.pone.0205822
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author Ayers, John W.
Dredze, Mark
Leas, Eric C.
Caputi, Theodore L.
Allem, Jon-Patrick
Cohen, Joanna E.
author_facet Ayers, John W.
Dredze, Mark
Leas, Eric C.
Caputi, Theodore L.
Allem, Jon-Patrick
Cohen, Joanna E.
author_sort Ayers, John W.
collection PubMed
description News media monitoring is an important scientific tool. By treating news reporters as data collectors and their reports as qualitative accounts of a fast changing public health landscape, researchers can glean many valuable insights. Yet, there have been surprisingly few innovations in public health media monitoring, with nearly all studies relying on labor-intensive content analyses limited to a small number of media reports. We propose to advance this subfield by using scalable machine learning. In potentially the largest contemporary public health media monitoring study to date, we systematically characterize global news reports surrounding electronic cigarettes or electronic nicotine delivery systems (ENDS) using natural language processing techniques. News reports including ENDS terms (e.g., “electronic cigarettes”) from over 100,000 sources (all sources archived on Google News or Bing News, as well as all news articles shared on Twitter) were monitored for 1 January 2013 through 31 July 2018. The geographic and subject (e.g., prevalence, bans, quitting, warnings, marketing, prices, age, flavor and industry) foci of news articles, their popularity among readers who share news on social media, and the sentiment behind news articles were assessed algorithmically. Globally there were 86,872 ENDS news reports with coverage increasing from 8 (standard deviation [SD] = 8) stories per day in 2013 to 75 (SD = 56) stories per day during 2018. The focus of ENDS news spanned 148 nations, with the plurality focusing on the United States (34% of all news). Potentially overlooked hotspots of ENDS media activity included China, Egypt, Russia, Ukraine, and Paraguay. The most common subject was warnings about ENDS (18%), followed by bans on using ENDS (13%) and ENDS prices (9%). Flavor and age restrictions were the least covered news subjects (~1% each). Among different subject foci, reports on quitting cigarettes using ENDS had the highest probability of scoring in the top three deciles of popularity rankings. Moreover, ENDS news on quitting and prices had a more positive sentiment on average than news with other subject foci. Public health leaders can use these trends to stay abreast of how ENDS are portrayed in the media, and potentially how the public perceives ENDS. Because our analytical strategies are updated in near real time, we aim to make media monitoring part of standard practice to support evidence-based tobacco control in the future.
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spelling pubmed-62145102018-11-19 Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018 Ayers, John W. Dredze, Mark Leas, Eric C. Caputi, Theodore L. Allem, Jon-Patrick Cohen, Joanna E. PLoS One Research Article News media monitoring is an important scientific tool. By treating news reporters as data collectors and their reports as qualitative accounts of a fast changing public health landscape, researchers can glean many valuable insights. Yet, there have been surprisingly few innovations in public health media monitoring, with nearly all studies relying on labor-intensive content analyses limited to a small number of media reports. We propose to advance this subfield by using scalable machine learning. In potentially the largest contemporary public health media monitoring study to date, we systematically characterize global news reports surrounding electronic cigarettes or electronic nicotine delivery systems (ENDS) using natural language processing techniques. News reports including ENDS terms (e.g., “electronic cigarettes”) from over 100,000 sources (all sources archived on Google News or Bing News, as well as all news articles shared on Twitter) were monitored for 1 January 2013 through 31 July 2018. The geographic and subject (e.g., prevalence, bans, quitting, warnings, marketing, prices, age, flavor and industry) foci of news articles, their popularity among readers who share news on social media, and the sentiment behind news articles were assessed algorithmically. Globally there were 86,872 ENDS news reports with coverage increasing from 8 (standard deviation [SD] = 8) stories per day in 2013 to 75 (SD = 56) stories per day during 2018. The focus of ENDS news spanned 148 nations, with the plurality focusing on the United States (34% of all news). Potentially overlooked hotspots of ENDS media activity included China, Egypt, Russia, Ukraine, and Paraguay. The most common subject was warnings about ENDS (18%), followed by bans on using ENDS (13%) and ENDS prices (9%). Flavor and age restrictions were the least covered news subjects (~1% each). Among different subject foci, reports on quitting cigarettes using ENDS had the highest probability of scoring in the top three deciles of popularity rankings. Moreover, ENDS news on quitting and prices had a more positive sentiment on average than news with other subject foci. Public health leaders can use these trends to stay abreast of how ENDS are portrayed in the media, and potentially how the public perceives ENDS. Because our analytical strategies are updated in near real time, we aim to make media monitoring part of standard practice to support evidence-based tobacco control in the future. Public Library of Science 2018-11-02 /pmc/articles/PMC6214510/ /pubmed/30388126 http://dx.doi.org/10.1371/journal.pone.0205822 Text en © 2018 Ayers et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ayers, John W.
Dredze, Mark
Leas, Eric C.
Caputi, Theodore L.
Allem, Jon-Patrick
Cohen, Joanna E.
Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018
title Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018
title_full Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018
title_fullStr Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018
title_full_unstemmed Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018
title_short Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018
title_sort next generation media monitoring: global coverage of electronic nicotine delivery systems (electronic cigarettes) on bing, google and twitter, 2013-2018
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6214510/
https://www.ncbi.nlm.nih.gov/pubmed/30388126
http://dx.doi.org/10.1371/journal.pone.0205822
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