Cargando…

Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach

BACKGROUND: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass me...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Qian, Zheng, Zequan, Zheng, Jiabin, Chen, Qiuyi, Liu, Guan, Chen, Sihan, Chu, Bojia, Zhu, Hongyu, Akinwunmi, Babatunde, Huang, Jian, Zhang, Casper J P, Ming, Wai-Kit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189789/
https://www.ncbi.nlm.nih.gov/pubmed/32302966
http://dx.doi.org/10.2196/19118
_version_ 1783527565232701440
author Liu, Qian
Zheng, Zequan
Zheng, Jiabin
Chen, Qiuyi
Liu, Guan
Chen, Sihan
Chu, Bojia
Zhu, Hongyu
Akinwunmi, Babatunde
Huang, Jian
Zhang, Casper J P
Ming, Wai-Kit
author_facet Liu, Qian
Zheng, Zequan
Zheng, Jiabin
Chen, Qiuyi
Liu, Guan
Chen, Sihan
Chu, Bojia
Zhu, Hongyu
Akinwunmi, Babatunde
Huang, Jian
Zhang, Casper J P
Ming, Wai-Kit
author_sort Liu, Qian
collection PubMed
description BACKGROUND: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE: The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS: We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS: After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS: Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.
format Online
Article
Text
id pubmed-7189789
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-71897892020-05-01 Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach Liu, Qian Zheng, Zequan Zheng, Jiabin Chen, Qiuyi Liu, Guan Chen, Sihan Chu, Bojia Zhu, Hongyu Akinwunmi, Babatunde Huang, Jian Zhang, Casper J P Ming, Wai-Kit J Med Internet Res Original Paper BACKGROUND: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE: The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS: We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS: After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS: Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data. JMIR Publications 2020-04-28 /pmc/articles/PMC7189789/ /pubmed/32302966 http://dx.doi.org/10.2196/19118 Text en ©Qian Liu, Zequan Zheng, Jiabin Zheng, Qiuyi Chen, Guan Liu, Sihan Chen, Bojia Chu, Hongyu Zhu, Babatunde Akinwunmi, Jian Huang, Casper J P Zhang, Wai-Kit Ming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.04.2020. 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 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
Liu, Qian
Zheng, Zequan
Zheng, Jiabin
Chen, Qiuyi
Liu, Guan
Chen, Sihan
Chu, Bojia
Zhu, Hongyu
Akinwunmi, Babatunde
Huang, Jian
Zhang, Casper J P
Ming, Wai-Kit
Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
title Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
title_full Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
title_fullStr Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
title_full_unstemmed Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
title_short Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
title_sort health communication through news media during the early stage of the covid-19 outbreak in china: digital topic modeling approach
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189789/
https://www.ncbi.nlm.nih.gov/pubmed/32302966
http://dx.doi.org/10.2196/19118
work_keys_str_mv AT liuqian healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT zhengzequan healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT zhengjiabin healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT chenqiuyi healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT liuguan healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT chensihan healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT chubojia healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT zhuhongyu healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT akinwunmibabatunde healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT huangjian healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT zhangcasperjp healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach
AT mingwaikit healthcommunicationthroughnewsmediaduringtheearlystageofthecovid19outbreakinchinadigitaltopicmodelingapproach