The Response of Governments and Public Health Agencies to COVID-19 Pandemics on Social Media: A Multi-Country Analysis of Twitter Discourse

BackgroundA significant public health emergency has appeared worldwide since the beginning of 2020. The spread of negative information about COVID-19 on social media poses a challenge and threat to public health disposition and the credibility of government public opinion.ObjectiveThis study aimed to analyze the rules and characteristics of government media in disseminating information on public emergencies. In addition, find ways and means to improve government media's communication power and credibility.MethodBased on relevant theories and measures of information econometrics, 10 WeChat official accounts of the Chinese government were taken as examples. The Python crawler tool was used to collect data of 10 WeChat official accounts-related tweets. In addition, this study used various tools, such as ROST, UCINET, and SPSS, for statistical analysis and co-word analysis of the data.ResultFrom January 17 to March 31, 2020, 6,612 COVID-19-related tweets were published by 10 WeChat official accounts, which broadcast epidemic overview, epidemic prevention and control, science and disinformation, epidemic assistance, epidemic impact, and negative impact. By analyzing the posting time and content of the tweets, we found that changes in the number of articles posted by the WeChat and changes in content and the progress of the COVID-19 pandemic are nearly synchronized, and most tweets are published at 8:00 am. Furthermore, based on the analytics of high dissemination index and high-frequency words, we propose that there is a significant correlation between the strength of independence and the credibility of the WeChat official account.ConclusionThe three elements of WeChat communication (value, interest, and moving) and the degree of independent innovation of public numbers impact the communication power and credibility of government media. First, if the articles published by the WeChat official account are valuable, interesting, and moving, the communication power of the WeChat official account would get more powerful. Second, increased ability for independent innovation has a positive impact on enhancing the WeChat official account's credibility. Third, government media can improve its governance effects of public health emergencies by enhancing their communication power and credibility.

Section: Introductionmentioning

confidence: 99%

Improving the Communication and Credibility of Government Media in Response to Public Health Emergencies: Analysis of Tweets From the WeChat Official Accounts of 10 Chinese Health Commissioners

Wang

Zhong

et al. 2022

“…Microblogs about COVID-19 were filtered from the full dataset based on a prior set of keywords related to the epidemic ( 39 , 40 ) (see Supplementary Textbox 1 ). After conducting text segmentation for these microblogs, we further ordered keywords of segmentation by the frequency of every keyword.…”

Section: Resultsmentioning

confidence: 99%

Network Structure and Community Evolution Online: Behavioral and Emotional Changes in Response to COVID-19

Fang

Wang

Tan

et al. 2022

Background: The measurement and identification of changes in the social structure in response to an exceptional event like COVID-19 can facilitate a more informed public response to the pandemic and provide fundamental insights on how collective social processes respond to extreme events.Objective: In this study, we built a generalized framework for applying social media data to understand public behavioral and emotional changes in response to COVID-19.Methods: Utilizing a complete dataset of Sina Weibo posts published by users in Wuhan from December 2019 to March 2020, we constructed a time-varying social network of 3.5 million users. In combination with community detection, text analysis, and sentiment analysis, we comprehensively analyzed the evolution of the social network structure, as well as the behavioral and emotional changes across four main stages of Wuhan's experience with the epidemic.Results: The empirical results indicate that almost all network indicators related to the network's size and the frequency of social interactions increased during the outbreak. The number of unique recipients, average degree, and transitivity increased by 24, 23, and 19% during the severe stage than before the outbreak, respectively. Additionally, the similarity of topics discussed on Weibo increased during the local peak of the epidemic. Most people began discussing the epidemic instead of the more varied cultural topics that dominated early conversations. The number of communities focused on COVID-19 increased by nearly 40 percent of the total number of communities. Finally, we find a statistically significant “rebound effect” by exploring the emotional content of the users' posts through paired sample t-test (P = 0.003).Conclusions: Following the evolution of the network and community structure can explain how collective social processes changed during the pandemic. These results can provide data-driven insights into the development of public attention during extreme events.

“…The endless rumors have brought more anxiety and distress in society than just the virus, and have inflicted great damage on people's enthusiasm to fight the pandemic ( 24 ). Therefore, it is essential to conduct targeted research into the Internet rumors that have been generated during this period ( 1 , 25 ), which will facilitate a better understanding of the real trends of COVID-19, avoid unnecessary anxiety, and restore normal social order and stability of society ( 26 ).…”

Section: Related Workmentioning

confidence: 99%

Internet Rumors During the COVID-19 Pandemic: Dynamics of Topics and Public Psychologies

Xiao

Huang

Zhang

et al. 2021

The capturing of social opinions, especially rumors, is a crucial issue in digital public health. With the outbreak of the COVID-19 pandemic, the discussions of related topics have increased exponentially in social media, with a large number of rumors on the Internet, which highly impede the harmony and sustainable development of society. As human health has never suffered a threat of this magnitude since the Internet era, past studies have lacked in-depth analysis of rumors regarding such a globally sweeping pandemic. This text-based analysis explores the dynamic features of Internet rumors during the COVID-19 pandemic considering the progress of the pandemic as time-series. Specifically, a Latent Dirichlet Allocation (LDA) model is used to extract rumor topics that spread widely during the pandemic, and the extracted six rumor topics, i.e., “Human Immunity,” “Technology R&D,” “Virus Protection,” “People's Livelihood,” “Virus Spreading,” and “Psychosomatic Health” are found to show a certain degree of concentrated distribution at different stages of the pandemic. Linguistic Inquiry and Word Count (LIWC) is used to statistically test the psychosocial dynamics reflected in the rumor texts, and the results show differences in psychosocial characteristics of rumors at different stages of the pandemic progression. There are also differences in the indicators of psychosocial characteristics between truth and disinformation. Our results reveal which topics of rumors and which psychosocial characteristics are more likely to spread at each stage of progress of the pandemic. The findings contribute to a comprehensive understanding of the changing public opinions and psychological dynamics during the pandemic, and also provide reference for public opinion responses to major public health emergencies that may arise in the future.