Cargando…

#Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis

E-cigarette use is increasing dramatically among adolescents as social media marketing portrays “vaping” products as healthier alternatives to conventional cigarettes. In September 2018, the Food and Drug Administration (FDA) launched an anti-vaping campaign, in U.S. high schools, on social media an...

Descripción completa

Detalles Bibliográficos
Autores principales: Vassey, Julia, Metayer, Catherine, Kennedy, Chris J., Whitehead, Todd P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883232/
https://www.ncbi.nlm.nih.gov/pubmed/35233388
http://dx.doi.org/10.3389/fcomm.2019.00075
_version_ 1784659877436588032
author Vassey, Julia
Metayer, Catherine
Kennedy, Chris J.
Whitehead, Todd P.
author_facet Vassey, Julia
Metayer, Catherine
Kennedy, Chris J.
Whitehead, Todd P.
author_sort Vassey, Julia
collection PubMed
description E-cigarette use is increasing dramatically among adolescents as social media marketing portrays “vaping” products as healthier alternatives to conventional cigarettes. In September 2018, the Food and Drug Administration (FDA) launched an anti-vaping campaign, in U.S. high schools, on social media and other platforms, emphasizing “The Real Cost” of e-cigarettes. Using a novel deep learning approach, we assessed changes in vaping-related content on Instagram from 2017 to 2019 and drew an inference about the initial impact of the FDA’s Real Cost campaign on Instagram. We collected 245,894 Instagram posts that used vaping-related hashtags (e.g., #vape, #ejuice) in four samples from 2017 to 2019. We compared the “like” count from these posts before and after the FDA campaign. We used deep learning image classification to analyze 49,655 Instagram image posts, separating images of men, women, and vaping devices. We also conducted text analysis and topic modeling to detect the common words and themes in the posted captions. Since September 2018, the FDA-sponsored hashtag #TheRealCost has been used about 50 times per month on Instagram, whereas vaping-related hashtags we tracked were used up to 10,000 times more often. Comparing the pre-intervention (2017, 2018) and post-intervention (2019) samples of vaping-related Instagram posts, we found a three-fold increase in the median “like” count (10 vs. 28) and a 6-fold increase in the proportion of posts with more than 100 likes (2 vs. 15%). Over 70% of Instagram vaping images featured e-juices and devices, with a growing number of images depicting a “pod,” the type of discrete vaping device that delivers high concentration of nicotine and is favored by novice e-cigarette users. In addition, the Instagram analytics data shared by the vaping influencers we interviewed showed underage Instagram users among their followers.
format Online
Article
Text
id pubmed-8883232
institution National Center for Biotechnology Information
language English
publishDate 2020
record_format MEDLINE/PubMed
spelling pubmed-88832322022-02-28 #Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis Vassey, Julia Metayer, Catherine Kennedy, Chris J. Whitehead, Todd P. Front Commun (Lausanne) Article E-cigarette use is increasing dramatically among adolescents as social media marketing portrays “vaping” products as healthier alternatives to conventional cigarettes. In September 2018, the Food and Drug Administration (FDA) launched an anti-vaping campaign, in U.S. high schools, on social media and other platforms, emphasizing “The Real Cost” of e-cigarettes. Using a novel deep learning approach, we assessed changes in vaping-related content on Instagram from 2017 to 2019 and drew an inference about the initial impact of the FDA’s Real Cost campaign on Instagram. We collected 245,894 Instagram posts that used vaping-related hashtags (e.g., #vape, #ejuice) in four samples from 2017 to 2019. We compared the “like” count from these posts before and after the FDA campaign. We used deep learning image classification to analyze 49,655 Instagram image posts, separating images of men, women, and vaping devices. We also conducted text analysis and topic modeling to detect the common words and themes in the posted captions. Since September 2018, the FDA-sponsored hashtag #TheRealCost has been used about 50 times per month on Instagram, whereas vaping-related hashtags we tracked were used up to 10,000 times more often. Comparing the pre-intervention (2017, 2018) and post-intervention (2019) samples of vaping-related Instagram posts, we found a three-fold increase in the median “like” count (10 vs. 28) and a 6-fold increase in the proportion of posts with more than 100 likes (2 vs. 15%). Over 70% of Instagram vaping images featured e-juices and devices, with a growing number of images depicting a “pod,” the type of discrete vaping device that delivers high concentration of nicotine and is favored by novice e-cigarette users. In addition, the Instagram analytics data shared by the vaping influencers we interviewed showed underage Instagram users among their followers. 2020 2020-01-22 /pmc/articles/PMC8883232/ /pubmed/35233388 http://dx.doi.org/10.3389/fcomm.2019.00075 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Article
Vassey, Julia
Metayer, Catherine
Kennedy, Chris J.
Whitehead, Todd P.
#Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis
title #Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis
title_full #Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis
title_fullStr #Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis
title_full_unstemmed #Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis
title_short #Vape: Measuring E-Cigarette Influence on Instagram With Deep Learning and Text Analysis
title_sort #vape: measuring e-cigarette influence on instagram with deep learning and text analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883232/
https://www.ncbi.nlm.nih.gov/pubmed/35233388
http://dx.doi.org/10.3389/fcomm.2019.00075
work_keys_str_mv AT vasseyjulia vapemeasuringecigaretteinfluenceoninstagramwithdeeplearningandtextanalysis
AT metayercatherine vapemeasuringecigaretteinfluenceoninstagramwithdeeplearningandtextanalysis
AT kennedychrisj vapemeasuringecigaretteinfluenceoninstagramwithdeeplearningandtextanalysis
AT whiteheadtoddp vapemeasuringecigaretteinfluenceoninstagramwithdeeplearningandtextanalysis