Cargando…

Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach

BACKGROUND: Thirdhand smoke has been a growing topic for years in China. Thirdhand smoke (THS) consists of residual tobacco smoke pollutants that remain on surfaces and in dust. These pollutants are re-emitted as a gas or react with oxidants and other compounds in the environment to yield secondary...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Qian, Chen, Qiuyi, Shen, Jiayi, Wu, Huailiang, Sun, Yimeng, Ming, Wai-Kit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371067/
https://www.ncbi.nlm.nih.gov/pubmed/30694199
http://dx.doi.org/10.2196/12414
_version_ 1783394494133043200
author Liu, Qian
Chen, Qiuyi
Shen, Jiayi
Wu, Huailiang
Sun, Yimeng
Ming, Wai-Kit
author_facet Liu, Qian
Chen, Qiuyi
Shen, Jiayi
Wu, Huailiang
Sun, Yimeng
Ming, Wai-Kit
author_sort Liu, Qian
collection PubMed
description BACKGROUND: Thirdhand smoke has been a growing topic for years in China. Thirdhand smoke (THS) consists of residual tobacco smoke pollutants that remain on surfaces and in dust. These pollutants are re-emitted as a gas or react with oxidants and other compounds in the environment to yield secondary pollutants. OBJECTIVE: Collecting media reports on THS from major media outlets and analyzing this subject using topic modeling can facilitate a better understanding of the role that the media plays in communicating this health issue to the public. METHODS: The data were retrieved from the Wiser and Factiva news databases. A preliminary investigation focused on articles dated between January 1, 2013, and December 31, 2017. Use of Latent Dirichlet Allocation yielded the top 10 topics about THS. The use of the modified LDAvis tool enabled an overall view of the topic model, which visualizes different topics as circles. Multidimensional scaling was used to represent the intertopic distances on a two-dimensional plane. RESULTS: We found 745 articles dated between January 1, 2013, and December 31, 2017. The United States ranked first in terms of publications (152 articles on THS from 2013-2017). We found 279 news reports about THS from the Chinese media over the same period and 363 news reports from the United States. Given our analysis of the percentage of news related to THS in China, Topic 1 (Cancer) was the most popular among the topics and was mentioned in 31.9% of all news stories. Topic 2 (Control of quitting smoking) was related to roughly 15% of news items on THS. CONCLUSIONS: Data analysis and the visualization of news articles can generate useful information. Our study shows that topic modeling can offer insights into understanding news reports related to THS. This analysis of media trends indicated that related diseases, air and particulate matter (PM(2.5)), and control and restrictions are the major concerns of the Chinese media reporting on THS. The Chinese press still needs to consider fuller reports on THS based on scientific evidence and with less focus on sensational headlines. We recommend that additional studies be conducted related to sentiment analysis of news data to verify and measure the influence of THS-related topics.
format Online
Article
Text
id pubmed-6371067
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-63710672019-02-27 Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach Liu, Qian Chen, Qiuyi Shen, Jiayi Wu, Huailiang Sun, Yimeng Ming, Wai-Kit JMIR Med Inform Original Paper BACKGROUND: Thirdhand smoke has been a growing topic for years in China. Thirdhand smoke (THS) consists of residual tobacco smoke pollutants that remain on surfaces and in dust. These pollutants are re-emitted as a gas or react with oxidants and other compounds in the environment to yield secondary pollutants. OBJECTIVE: Collecting media reports on THS from major media outlets and analyzing this subject using topic modeling can facilitate a better understanding of the role that the media plays in communicating this health issue to the public. METHODS: The data were retrieved from the Wiser and Factiva news databases. A preliminary investigation focused on articles dated between January 1, 2013, and December 31, 2017. Use of Latent Dirichlet Allocation yielded the top 10 topics about THS. The use of the modified LDAvis tool enabled an overall view of the topic model, which visualizes different topics as circles. Multidimensional scaling was used to represent the intertopic distances on a two-dimensional plane. RESULTS: We found 745 articles dated between January 1, 2013, and December 31, 2017. The United States ranked first in terms of publications (152 articles on THS from 2013-2017). We found 279 news reports about THS from the Chinese media over the same period and 363 news reports from the United States. Given our analysis of the percentage of news related to THS in China, Topic 1 (Cancer) was the most popular among the topics and was mentioned in 31.9% of all news stories. Topic 2 (Control of quitting smoking) was related to roughly 15% of news items on THS. CONCLUSIONS: Data analysis and the visualization of news articles can generate useful information. Our study shows that topic modeling can offer insights into understanding news reports related to THS. This analysis of media trends indicated that related diseases, air and particulate matter (PM(2.5)), and control and restrictions are the major concerns of the Chinese media reporting on THS. The Chinese press still needs to consider fuller reports on THS based on scientific evidence and with less focus on sensational headlines. We recommend that additional studies be conducted related to sentiment analysis of news data to verify and measure the influence of THS-related topics. JMIR Publications 2019-01-29 /pmc/articles/PMC6371067/ /pubmed/30694199 http://dx.doi.org/10.2196/12414 Text en ©Qian Liu, Qiuyi Chen, Jiayi Shen, Huailiang Wu, Yimeng Sun, Wai-Kit Ming. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 29.01.2019. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Liu, Qian
Chen, Qiuyi
Shen, Jiayi
Wu, Huailiang
Sun, Yimeng
Ming, Wai-Kit
Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach
title Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach
title_full Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach
title_fullStr Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach
title_full_unstemmed Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach
title_short Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach
title_sort data analysis and visualization of newspaper articles on thirdhand smoke: a topic modeling approach
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371067/
https://www.ncbi.nlm.nih.gov/pubmed/30694199
http://dx.doi.org/10.2196/12414
work_keys_str_mv AT liuqian dataanalysisandvisualizationofnewspaperarticlesonthirdhandsmokeatopicmodelingapproach
AT chenqiuyi dataanalysisandvisualizationofnewspaperarticlesonthirdhandsmokeatopicmodelingapproach
AT shenjiayi dataanalysisandvisualizationofnewspaperarticlesonthirdhandsmokeatopicmodelingapproach
AT wuhuailiang dataanalysisandvisualizationofnewspaperarticlesonthirdhandsmokeatopicmodelingapproach
AT sunyimeng dataanalysisandvisualizationofnewspaperarticlesonthirdhandsmokeatopicmodelingapproach
AT mingwaikit dataanalysisandvisualizationofnewspaperarticlesonthirdhandsmokeatopicmodelingapproach