Examining Social Media Crisis Communication during Early COVID-19 from Public Health and News Media for Quality, Content, and Corresponding Public Sentiment.
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SUBMITTER: MacKay M
PROVIDER: S-EPMC8345485 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:The coronavirus disease (COVID-19) has posed an unprecedented challenge to governments worldwide. Effective government communication of COVID-19 information with the public is of crucial importance. OBJECTIVE:We investigate how the most-read state-owned newspaper in China, People's Daily, used an online social networking site, Sina Weibo, to communicate about COVID-19 and whether this could engage the public. The objective of this study is to develop an integrated framework to examine the content, message style, and interactive features of COVID-19-related posts and determine their effects on public engagement in the largest social media network in China. METHODS:Content analysis was employed to scrutinize 608 COVID-19 posts, and coding was performed on three main dimensions: content, message style, and interactive features. The content dimension was coded into six subdimensions: action, new evidence, reassurance, disease prevention, health care services, and uncertainty, and the style dimension was coded into the subdimensions of narrative and nonnarrative. As for interactive features, they were coded into links to external sources, use of hashtags, use of questions to solicit feedback, and use of multimedia. Public engagement was measured in the form of the number of shares, comments, and likes on the People's Daily's Sina Weibo account from January 20, 2020, to March 11, 2020, to reveal the association between different levels of public engagement and communication strategies. A one-way analysis of variance followed by a post-hoc Tukey test and negative binomial regression analysis were employed to generate the results. RESULTS:We found that although the content frames of action, new evidence, and reassurance delivered in a nonnarrative style were predominant in COVID-19 communication by the government, posts related to new evidence and a nonnarrative style were strong negative predictors of the number of shares. In terms of generating a high number of shares, it was found that disease prevention posts delivered in a narrative style were able to achieve this purpose. Additionally, an interaction effect was found between content and style. The use of a narrative style in disease prevention posts had a significant positive effect on generating comments and likes by the Chinese public, while links to external sources fostered sharing. CONCLUSIONS:These results have implications for governments, health organizations, medical professionals, the media, and researchers on their epidemic communication to engage the public. Selecting suitable communication strategies may foster active liking and sharing of posts on social media, which in turn, might raise the public's awareness of COVID-19 and motivate them to take preventive measures. The sharing of COVID-19 posts is particularly important because this action can reach out to a large audience, potentially helping to contain the spread of the virus.
| S-EPMC7446717 | biostudies-literature
Project description:BackgroundThe COVID-19 health crisis has posed an unprecedented challenge for governments worldwide to manage and communicate about the pandemic effectively, while maintaining public trust. Good leadership image in times of a health emergency is paramount to ensure public confidence in governments' abilities to manage the crisis.ObjectiveThe aim of this study was to identify types of image repair strategies utilized by the Malaysian government in their communication about COVID-19 in the media and analyze public responses to these messages on social media.MethodsContent analysis was employed to analyze 120 media statements and 382 comments retrieved from Facebook pages of 2 mainstream newspapers-Berita Harian and The Star. These media statements and comments were collected within a span of 6 weeks prior to and during the first implementation of Movement Control Order by the Malaysian Government. The media statements were analyzed according to Image Repair Theory to categorize strategies employed in government communications related to COVID-19 crisis. Public opinion responses were measured using modified lexicon-based sentiment analysis to categorize positive, negative, and neutral statements.ResultsThe Malaysian government employed all 5 Image Repair Theory strategies in their communications in both newspapers. The strategy most utilized was reducing offensiveness (75/120, 62.5%), followed by corrective action (30/120, 25.0%), evading responsibilities (10/120, 8.3%), denial (4/120, 3.3%), and mortification (1/120, 0.8%). This study also found multiple substrategies in government media statements including denial, shifting blame, provocation, defeasibility, accident, good intention, bolstering, minimization, differentiation, transcendence, attacking accuser, resolve problem, prevent recurrence, admit wrongdoing, and apologize. This study also found that 64.7% of public opinion was positive in response to media statements made by the Malaysian government and also revealed a significant positive association (P=.04) between image repair strategies utilized by the Malaysian government and public opinion.ConclusionsCommunication in the media may assist the government in fostering positive support from the public. Suitable image repair strategies could garner positive public responses and help build trust in times of crisis.
| S-EPMC8341088 | biostudies-literature
Project description:We investigated the content of liberal and conservative news media Facebook posts on race and ethnic health disparities. A total of 3,327,360 liberal and conservative news Facebook posts from the United States (US) from January 2015 to May 2022 were collected from the Crowd Tangle platform and filtered for race and health-related keywords. Qualitative content analysis was conducted on a random sample of 1750 liberal and 1750 conservative posts. Posts were analyzed for a continuum of hate speech using a newly developed method combining faceted Rasch item response theory with deep learning. Across posts referencing Asian, Black, Latinx, Middle Eastern, and immigrants/refugees, liberal news posts had lower hate scores compared to conservative posts. Liberal news posts were more likely to acknowledge and detail the existence of racial/ethnic health disparities, while conservative news posts were more likely to highlight the negative consequences of protests, immigration, and the disenfranchisement of Whites. Facebook posts from liberal and conservative news focus on different themes with fewer discussions of racial inequities in conservative news. Investigating the discourse on race and health in social media news posts may inform our understanding of the public's exposure to and knowledge of racial health disparities, and policy-level support for ameliorating these disparities.
| S-EPMC9960309 | biostudies-literature
Project description:Stringent containment and closure policies have been widely implemented by governments to prevent the transmission of COVID-19. Yet, such policies have significant impacts on people’s emotions and mental well-being. Here, we study the effects of pandemic containment policies on public sentiment in Singapore. We computed daily sentiment values scaled from −1 to 1, using high-frequency data of ∼240,000 posts from highly followed public Facebook groups during January to November 2020. The lockdown in April saw a 0.1 unit rise in daily average sentiment, followed by a 0.2 unit increase with partially lifting of lockdown in June, and a 0.15 unit fall after further easing of restrictions in August. Regarding the impacts of specific containment measures, a 0.13 unit fall in sentiment was associated with travel restrictions, whereas a 0.18 unit rise was related to introducing a facial covering policy at the start of the pandemic. A 0.15 unit fall in sentiment was linked to restrictions on public events, post lock-down. Virus infection, wearing masks, salary, and jobs were the chief concerns found in the posts. A 2 unit increase in these concerns occurred even when some restrictions were eased in August 2020. During pandemics, monitoring public sentiment and concerns through social media supports policymakers in multiple ways. First, the method given here is a near real-time scalable solution to study policy impacts. Second, it aids in data-driven and evidence-based revision of existing policies and implementation of similar policies in the future. Third, it identifies public concerns following policy changes, addressing which can increase trust in governments and improve public sentiment.
| S-EPMC9171635 | biostudies-literature
Project description:BackgroundThe proliferation of misinformation on social media is a significant concern due to its frequent occurrence and subsequent adverse social consequences. Effective interventions for and corrections of misinformation have become a focal point of scholarly inquiry. However, exploration of the underlying causes that affect the public acceptance of misinformation correction is still important and not yet sufficient.ObjectiveThis study aims to identify the critical attributions that influence public acceptance of misinformation correction by using attribution analysis of aspects of public sentiment, as well as investigate the differences and similarities in public sentiment attributions in different types of misinformation correction.MethodsA theoretical framework was developed for analysis based on attribution theory, and public sentiment attributions were divided into 6 aspects and 11 dimensions. The correction posts for the 31 screened misinformation events comprised 33,422 Weibo posts, and the corresponding Weibo comments amounted to 370,218. A pretraining model was used to assess public acceptance of misinformation correction from these comments, and the aspect-based sentiment analysis method was used to identify the attributions of public sentiment response. Ultimately, this study revealed the causality between public sentiment attributions and public acceptance of misinformation correction through logistic regression analysis.ResultsThe findings were as follows: First, public sentiments attributed to external attribution had a greater impact on public acceptance than those attributed to internal attribution. The public associated different aspects with correction depending on the type of misinformation. The accuracy of the correction and the entity responsible for carrying it out had a significant impact on public acceptance of misinformation correction. Second, negative sentiments toward the media significantly increased, and public trust in the media significantly decreased. The collapse of media credibility had a detrimental effect on the actual effectiveness of misinformation correction. Third, there was a significant difference in public attitudes toward the official government and local governments. Public negative sentiments toward local governments were more pronounced.ConclusionsOur findings imply that public acceptance of misinformation correction requires flexible communication tailored to public sentiment attribution. The media need to rebuild their image and regain public trust. Moreover, the government plays a central role in public acceptance of misinformation correction. Some local governments need to repair trust with the public. Overall, this study offered insights into practical experience and a theoretical foundation for controlling various types of misinformation based on attribution analysis of public sentiment.
| S-EPMC11364945 | biostudies-literature
Project description:BackgroundPrior research suggests that social media-based public health campaigns are often targeted by countercampaigns.ObjectiveUsing reactance theory as the theoretical framework, this research characterizes the nature of public response to tobacco prevention messages disseminated via a social media-based campaign. We also examine whether agreement with the prevention messages is associated with comment tone and nature of the contribution to the overall discussion.MethodsUser comments to tobacco prevention messages, posted between April 19, 2017 and July 12, 2017, were extracted from Twitter, Facebook, and Instagram. Two coders categorized comments in terms of tone, agreement with message, nature of contribution, mentions of government agency and regulation, promotional or spam comments, and format of comment. Chi-square analyses tested associations between agreement with the message and tone of the public response and the nature of contributions to the discussions.ResultsOf the 1242 comments received (Twitter: n=1004; Facebook: n=176; Instagram: n=62), many comments used a negative tone (42.75%) and disagreed with the health messages (39.77%), while the majority made healthy contributions to the discussions (84.38%). Only 0.56% of messages mentioned government agencies, and only 0.48% of the comments were antiregulation. Comments employing a positive tone (84.13%) or making healthy contributions (69.11%) were more likely to agree with the campaign messages (P=0.01). Comments employing a negative tone (71.25%) or making toxic contributions (36.26%) generally disagreed with the messages (P=0.01).ConclusionsThe majority of user comments in response to a tobacco prevention campaign made healthy contributions. Our findings encourage the use of social media to promote dialogue about controversial health topics such as smoking. However, toxicity was characteristic of comments that disagreed with the health messages. Managing negative and toxic comments on social media is a crucial issue for social media-based tobacco prevention campaigns to consider.
| S-EPMC7752523 | biostudies-literature
Project description:BackgroundDementia is a global public health priority due to rapid growth of the aging population. As China has the world's largest population with dementia, this debilitating disease has created tremendous challenges for older adults, family caregivers, and health care systems on the mainland nationwide. However, public awareness and knowledge of the disease remain limited in Chinese society.ObjectiveThis study examines online public discourse and sentiment toward dementia among the Chinese public on a leading Chinese social media platform Weibo. Specifically, this study aims to (1) assess and examine public discourse and sentiment toward dementia among the Chinese public, (2) determine the extent to which dementia-related discourse and sentiment vary among different user groups (ie, government, journalists/news media, scientists/experts, and the general public), and (3) characterize temporal trends in public discourse and sentiment toward dementia among different user groups in China over the past decade.MethodsIn total, 983,039 original dementia-related posts published by 347,599 unique users between 2010 and 2021, together with their user information, were analyzed. Machine learning analytical techniques, including topic modeling, sentiment analysis, and semantic network analyses, were used to identify salient themes/topics and their variations across different user groups (ie, government, journalists/news media, scientists/experts, and the general public).ResultsTopic modeling results revealed that symptoms, prevention, and social support are the most prevalent dementia-related themes on Weibo. Posts about dementia policy/advocacy have been increasing in volume since 2018. Raising awareness is the least discussed topic over time. Sentiment analysis indicated that Weibo users generally attach negative attitudes/emotions to dementia, with the general public holding a more negative attitude than other user groups.ConclusionsOverall, dementia has received greater public attention on social media since 2018. In particular, discussions related to dementia advocacy and policy are gaining momentum in China. However, disparaging language is still used to describe dementia in China; therefore, a nationwide initiative is needed to alter the public discourse on dementia. The results contribute to previous research by providing a macrolevel understanding of the Chinese public's discourse and attitudes toward dementia, which is essential for building national education and policy initiatives to create a dementia-friendly society. Our findings indicate that dementia is associated with negative sentiments, and symptoms and prevention dominate public discourse. The development of strategies to address unfavorable perceptions of dementia requires policy and public health attention. The results further reveal that an urgent need exists to increase public knowledge about dementia. Social media platforms potentially could be leveraged for future dementia education interventions to increase dementia awareness and promote positive attitudes.
| S-EPMC9482068 | biostudies-literature
Project description:BackgroundSouth Africa was the first sub-Saharan African country to implement a sugar-sweetened beverage (SSB) tax called the Health Promotion Levy (HPL) in April 2018. Given news media can increase public awareness and sway opinions, this study analyzed how the media represented the HPL, including expressions of support or challenge, topics associated with the levy, and stakeholder views of the HPL.MethodsWe performed a quantitative content analysis of online South African news articles related to the HPL published between January 1, 2017 and June 30, 2019. We coded the presence or absence of mentions related to health and economic effects of the HPL and HPL support or opposition. Prevalence of these mentions, overall and by source (industry, government, academics, other), were analyzed with Pearson χ2 and post-hoc Fisher exact tests.ResultsAcross all articles, 81% mentioned health, and 65% mentioned economics topics. 54% of articles expressed support, 26% opposition, and 20% a balanced view of the HPL. All sources except industry expressed majority support for the HPL. Health reasons were the most common justifications for support, and economic harms were the most common justifications for opposition. Statements that sugar intake is not related to obesity, the HPL will not reduce SSB intake, and the HPL will cause industry or economic harm were all disproportionately high in industry sources (92, 80, and 81% vs 25% prevalence in total sample) (p < 0.001). Statements that sugar intake is related to obesity and non-communicable diseases were disproportionately high in both government (46 and 54% vs 31% prevalence in total sample) (p < 0.001) and academics (33 and 38% vs 25% prevalence in total sample) (p < 0.05). Statements that the HPL will improve health and the HPL will reduce health care costs were disproportionately high in government (47% vs 31% prevalence in total sample) (p < 0.001) and academics (44% vs 25% prevalence in total sample) (p < 0.05), respectively.ConclusionsIndustry expressed no support for the HPL, whereas academics, government, and other sources mainly expressed support. Future studies would be improved by linking news media exposure to SSB intake data to better understand the effects news media may have on individual behavior change.
| S-EPMC7937301 | biostudies-literature
Project description:Social networking sites offer an important means for increasing the accessibility and enabling new forms of health communication between the public and medical social influencers (MSIs). MSIs have a social presence and are perceived as a credible source of health-related information. A research gap, however, exists in understanding the communication strategies employed by MSIs and the factors driving the public to engage in health communication with MSIs. This study, therefore, developed a new conceptual framework incorporating health communication, dialogic and interpersonal communication by employing quantitative content analysis to examine public engagement with MSI communication on the largest microblogging site in China, Sina Weibo. The analysis yielded insights into how the usefulness of health-related information provided alongside the interactive dialogue and affective practices played an active role in engaging the public. The public sought health-related information primarily to address issues of concern for well-being and a high level of engagement in terms of online shares, likes, and comments was found. The use of multimedia made the site more appealing, resulting in likes while the expression of emotions by MSIs generated likes and comments. The need to connect with other online users and have a sense of community was reflected in engagement through sharing useful MSI posts by the public. By identifying influential MSIs on social networking sites, health information providers such as organizations and the government can raise awareness of health issues to foster a healthy lifestyle and contribute to better living in the community.
| S-EPMC7540861 | biostudies-literature
Project description:IntroductionNews media play an important role in raising public awareness, framing public opinions, affecting policy formulation, and acknowledgment of public health issues. Traditional qualitative content analysis for news sentiments and focuses are time-consuming and may not efficiently convey sentiments nor the focuses of news media.MethodsWe used descriptive statistics and state-of-art text mining to conduct sentiment analysis and topic modeling, to efficiently analyze over 3 million Reuters news articles during 2007-2017 for identifying their coverage, sentiments, and focuses for public health issues. Based on the top keywords from public health scientific journals, we identified 10 major public health issues (i.e., "air pollution," "alcohol drinking," "asthma," "depression," "diet," "exercise," "obesity," "pregnancy," "sexual behavior," and "smoking").ResultsThe news coverage for seven public health issues, "Smoking," "Exercise," "Alcohol drinking," "Diet," "Obesity," "Depression," and "Asthma" decreased over time. The news coverage for "Sexual behavior," "Pregnancy," and "Air pollution" fluctuated during 2007-2017. The sentiments of the news articles for three of the public health issues, "exercise," "alcohol drinking," and "diet" were predominately positive and associated such as "energy." Sentiments for the remaining seven public health issues were mainly negative, linked to negative terms, e.g., diseases. The results of topic modeling reflected the media's focus on public health issues.ConclusionsText mining methods may address the limitations of traditional qualitative approaches. Using big data to understand public health needs is a novel approach that could help clinical and translational science awards programs focus on community-engaged research efforts to address community priorities.
| S-EPMC8057471 | biostudies-literature