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      The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19)

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      Publication date (Electronic):
      Journal: PLOS ONE
      Publisher: Public Library of Science

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          Abstract

          Background and aims

          The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion.

          Methods

          We searched Baidu News using the keywords “Novel Coronavirus” and “COVID-19” from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data.

          Results

          We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event.

          Conclusions

          The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability.

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          Most cited references62

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          Fake News and COVID-19: Modelling the Predictors of Fake News Sharing Among Social Media Users

          Oberiri Destiny Apuke, Bahiyah Omar (2020)
          Highlights • Social media, fake news and COVID-19. • Misinformation on social media has fuelled panic among members of the public regarding the COVID-19. • Altruism is the strongest predictor of false news sharing on COVID-19 among social media users. • Information sharing, socialization, information seeking and pass time is positively associated with sharing false information on COVID-19. • Utilizing social media to entertain oneself is not associated with sharing fake news on COVID-19.
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            Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index

            Xue Gong, Yangyang Han, Mengchi Hou … (2020)
            Background The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies. Objective This study aims to use online search data (Baidu Index) to monitor the public’s attention and verify internet search engines’ function in public attention monitoring of public health emergencies. Methods We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention’s temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis. Results The Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases. Conclusions The national public’s demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public’s attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic.
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              Role of Media Coverage in Mitigating COVID-19 Transmission: Evidence from China

              Ning Liu, Zhuo Chen, Guoxian Bao (2020)
              Highlights • media coverage is associated with a reduction in the numbers of COVID-19 cases and close contacts • effect of media coverage on COVID-19 transmission was mediated by population mobility • number of cases and close contacts are related, with a stronger correlation early in the pandemic
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                Author and article information

                Contributors
                Xin Su: Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Shengwen Wang:
                ORCID: https://orcid.org/0000-0001-5911-2734
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SoftwareRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Joanna Rosak-Szyrocka: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Title: PLOS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 4 April 2024
                Publication date Collection: 2024
                Volume: 19
                Issue: 4
                Electronic Location Identifier: e0299374
                Affiliations
                [001] School of Business Administration, Shandong University of Finance and Economics, Jinan, Shandong Province, China
                Czestochowa University of Technology: Politechnika Czestochowska, POLAND
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-5911-2734
                Article
                Publisher ID: PONE-D-23-09860
                DOI: 10.1371/journal.pone.0299374
                PMC ID: 10994342
                PubMed ID: 38573976
                SO-VID: 135aedeb-7797-4f68-859a-f4da8371ab3e
                Copyright © © 2024 Su, Wang
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 2 April 2023
                Date accepted : 6 February 2024
                Page count
                Figures: 12, Tables: 7, Pages: 25
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100007129, Natural Science Foundation of Shandong Province;
                Award ID: ZR2020MG046
                Award Recipient :
                ORCID: https://orcid.org/0000-0001-5911-2734
                Funded by: funder-id http://dx.doi.org/10.13039/501100012456, National Social Science Fund of China;
                Award ID: 23BGL190
                Award Recipient :
                This research was supported by the National Social Science Fund of China (23BGL190), and Natural Science Foundation of Shandong Province (ZR2020MG046). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Medicine and Health Sciences
                Subject: Medical Conditions
                Subject: Infectious Diseases
                Subject: Viral Diseases
                Subject: Covid 19
                Subject: Medicine and Health Sciences
                Subject: Pulmonology
                Subject: Pneumonia
                Subject: Computer and Information Sciences
                Subject: Network Analysis
                Subject: Social Networks
                Subject: Social Sciences
                Subject: Sociology
                Subject: Social Networks
                Subject: Computer and Information Sciences
                Subject: Network Analysis
                Subject: Centrality
                Subject: Biology and Life Sciences
                Subject: Microbiology
                Subject: Virology
                Subject: Viral Transmission and Infection
                Subject: Computer and Information Sciences
                Subject: Information Theory
                Subject: Medicine and Health Sciences
                Subject: Epidemiology
                Subject: Social Epidemiology
                Subject: Medicine and Health Sciences
                Subject: Epidemiology
                Subject: Epidemiological Methods and Statistics
                Subject: Epidemiological Statistics
                Custom metadata
                Data Availability The data and code for this study are available as Supporting information. The data sets generated and analyzed during the current study are available via the protocols.io ( https://protocols.io/view/plosone-c5ify4bn), github ( https://github.com/ws8228/BaiduNews.git).
                Outbreaks COVID-19

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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