Examining risk and crisis communications of government agencies and stakeholders during early-stages of COVID-19 on Twitter

Emergency communication networks on Twitter during Hurricane Irma: information flow, influential actors, and top messages

This study combined network analysis with message-level content analysis to investigate patterns of information flow and to examine messages widely distributed on social media during Hurricane Irma of 2017. The results show that while organisational users and media professionals dominated the top 100 information sources, individual citizens played a critical role in information dissemination. Public agencies should increase their retweeting activities and share the information posted by other trustworthy sources; doing so will contribute to the timely exchange of vital information during a disaster. This study also identified the active involvement of nonprofit organisations as information brokers during the post-event stage, indicating the potential for emergency management organisations to integrate their communication efforts into those of nonprofit entities. These findings will inform emergency management practices regarding implementation of communication plans and policies, facilitate the embracement of new partner organisations, and help with establishing and sustaining effective communication ties with a wide range of stakeholders.

Comparative risk perception of the monkeypox outbreak and the monkeypox vaccine

Based on survey data collected from a nationally representative sample (N = 1,000), this study applies the psychometric paradigm to demonstrate that the American public perceived the monkeypox outbreak as a more dreaded risk than the monkeypox vaccine, but they also viewed the monkeypox vaccine as a more unknown risk. These perceptions influenced their overall risk judgment toward the monkeypox outbreak, support for public health responses and government assistance measures, and likelihood to get vaccinated. Contributing to research on risk perception, these findings indicate that the dread and unknown dimensions offer a more intricate assessment of risk perception beyond perceived susceptibility and perceived severity. Guiding risk communication practice, these results suggest that it is important to highlight to the public that the monkeypox vaccine is a mature technology and getting vaccinated before exposure provides the best protection for high-risk populations.

Influence of Strategic Crisis Communication on Public Perceptions during Public Health Crises: Insights from YouTube Chinese Media

Crisis communication plays a crucial role in preserving the national reputation during significant national crises. From the perspective of Situational Crisis Communication Theory (SCCT), this research paper analyzed over 1,790,816 YouTube comments from Chinese-speaking audiences, using sentiment analysis alongside the Difference-in-Differences (DiD) model, in order to investigate the influence of strategic crisis communication on public perceptions during public health crises. The study findings indicate that during this public health crisis, YouTube Chinese media, whose audience mainly consists of overseas Chinese-speaking users, primarily incorporated the enhancing strategies, succeeded by the diminish strategies, with limited application of deny strategies, while the use of rebuild strategies was virtually absent in this context. In addition, the research analysis confirms that Chinese media effectively increased the public's positive perceptions of crisis events through crisis communication. Particularly, enhancing strategies proved most effective in improving public perceptions, followed by diminish strategies. In contrast, deny strategies failed to influence public perceptions of the crisis, and rebuild strategies demonstrated a negative impact on public perception. Thus, the research findings of this paper extend essential insights for effectively managing potential public health crises in the future.

The role of social media in public health crises caused by infectious disease: a scoping review

IMPORTANCE

The onset of the COVID-19 global pandemic highlighted the increasing role played by social media in the generation, dissemination and consumption of outbreak-related information.

OBJECTIVE

The objective of the current review is to identify and summarise the role of social media in public health crises caused by infectious disease, using a five-step scoping review protocol.

EVIDENCE REVIEW

Keyword lists for two categories were generated: social media and public health crisis. By combining these keywords, an advanced search of various relevant databases was performed to identify all articles of interest from 2000 to 2021, with an initial retrieval date of 13 December 2021. A total of six medical and health science, psychology, social science and communication databases were searched: PubMed, Web of Science, Scopus, Embase, PsycINFO and CNKI. A three-stage screening process against inclusion and exclusion criteria was conducted.

FINDINGS

A total of 338 studies were identified for data extraction, with the earliest study published in 2010. Thematic analysis of the role of social media revealed three broad themes: surveillance monitoring, risk communication and disease control. Within these themes, 12 subthemes were also identified. Within surveillance monitoring, the subthemes were disease detection and prediction, public attitude and attention, public sentiment and mental health. Within risk communication, the subthemes were health advice, information-seeking behaviour, infodemics/misinformation circulation, seeking help online, online distance education and telehealth. Finally, within disease control, the subthemes were government response, public behaviour change and health education information quality. It was clear that the pace of research in this area has gradually increased over time as social media has evolved, with an explosion in attention following the outbreak of COVID-19.

CONCLUSIONS AND RELEVANCE

Social media has become a hugely powerful force in public health and cannot be ignored or viewed as a minor consideration when developing public health policy. Limitations of the study are discussed, along with implications for government, health authorities and individual users. The pressing need for government and health authorities to formalise evidence-based strategies for communicating via social media is highlighted, as well as issues for individual users in assessing the quality and reliability of information consumed on social media platforms.

Exploring determinants of formation of cognitive anchors from altruistic messages: A fuzzy DEMATEL approach

Altruistic communication by non-profit organizations plays a crucial role in shaping individuals' perceptions and beliefs about altruism. One of the indicators of effective communication is the anchoring of the messages. Therefore, understanding the underlying determinants of anchoring in altruistic communication is essential. Despite the importance of anchoring in the communication of altruism, extant research has not done much to examine the determinants of anchoring in altruistic communication. This paper investigates the determinants of anchoring in non-profit organizations' altruistic communication through the lens of the dual process theory. It applies the Fuzzy Decision Making Trial and Evaluation Laboratory (F-DEMATEL) method to analyze the causal and effect factors. Data were gathered from 12 social communication experts based in Taiwan. Out of the 12 proposed determinants, three factors, namely consistency, cultural consideration, and emotional anchoring, were established as significant causal factors. Consistency had causal effects on five other factors, namely, the use of metaphors, the use of antinomies, thematic anchoring, understanding the cognitive ability of the audience, and crafting engaging information. Cultural consideration had causal effects on feedback, naming, use of antinomies, thematic anchoring, emotional anchoring, and repetition. Emotional anchoring had causal effects on thematic anchoring, use of antinomies, use of metaphors, consistency, naming, feedback, understanding the cognitive ability of the audience, and repetition. On the other hand, feedback, naming, and use of antinomies were established as significant effect factors. The study's findings offer crucial contributions to the social communication literature and provide important insights for social communication practitioners.

The COVID-19 pandemic and seeking information about condoms online: an infodemiology approach

Objectives: As condoms are effective tools for pathogen-avoidance in sexual intercourse, seeking information about condoms online may be a reactive response to the COVID-19 according to the behavioral immune system theory.Design: Taking an infodemiology perspective, this research employed multilevel analyses to examine how COVID-19 online query data (i.e., Google topic search terms Coronavirus and COVID-19) and coronavirus epidemiological data (i.e., COVID-19 cases per million and case fatality rate) would predict condom information seeking behavior online (i.e., Google topic search term Condom) throughout the pandemic across American states (Study 1) and 102 countries/territories (Study 2), after accounting for death-thought accessibility (i.e., illness-related searches), interest in birth control (i.e., birth-control-related searches), COVID-19 control policy, stay at home behavior, season, religious holidays, yearly trends, autocorrelation, and contextual variables such as HIV prevalence rate and socioeconomic development indicators (GINI index, urbanization, etc.).Results: When there were high levels of COVID-19 concerns in cyberspace in a given week, search volume for condoms increased from the previous week across American states and different countries/territories. By contrast, the effect of actual coronavirus threat was non-significant.Conclusion: Seeking information about condoms online could be a reactive response to high levels of COVID-19 concerns across different populations.

Public health agencies' use of social media for communication during pandemics: a scoping review of the literature

Public health agencies (PHAs) have increasingly incorporated social media into their communication mix during successive pandemics in the 21st century. However, the quality, timing, and accuracy of their health messages have varied significantly, resulting in mixed outcomes for communication, audience engagement, and pandemic management. This study aimed to identify factors influencing the effectiveness of pandemic-related health messages shared by PHAs on social media and to report their impact on public engagement as documented in the literature. A scoping literature review was conducted following a predefined protocol. An electronic search of 7 relevant databases and 5 grey literature repositories yielded 9,714 papers published between January 2003 and November 2022. Seventy-three papers were deemed eligible and selected for review. The results underscored the insufficiency of social media guidance policies for PHAs. Six themes were identified: message source, message topic, message style, message timing, content credibility and reliability, and message recipient profile. These themes encompassed 20 variables that could inform PHAs' social media public health communication during pandemics. Additionally, the findings revealed potential interconnectedness among the variables, and this study concluded by proposing a conceptual model that expands upon existing theoretical foundations for developing and evaluating pandemic-related health messaging.

Sentiment analysis of epidemiological surveillance reports on COVID-19 in Greece using machine learning models

The present research deals with sentiment analysis performed with Microsoft Azure Machine Learning Studio to classify Facebook posts on the Greek National Public Health Organization (EODY) from November 2021 to January 2022 during the pandemic. Positive, negative and neutral sentiments were included after processing 300 reviews. This approach involved analyzing the words appearing in the comments and exploring the sentiments related to daily surveillance reports of COVID-19 published on the EODY Facebook page. Moreover, machine learning algorithms were implemented to predict the classification of sentiments. This research assesses the efficiency of a few popular machine learning models, which is one of the initial efforts in Greece in this domain. People have negative sentiments toward COVID surveillance reports. Words with the highest frequency of occurrence include government, vaccinated people, unvaccinated, telephone communication, health measures, virus, COVID-19 rapid/molecular tests, and of course, COVID-19. The experimental results disclose additionally that two classifiers, namely two class Neural Network and two class Bayes Point Machine, achieved high sentiment analysis accuracy and F1 score, particularly 87% and over 35%. A significant limitation of this study may be the need for more comparison with other research attempts that identified the sentiments of the EODY surveillance reports of COVID in Greece. Machine learning models can provide critical information combating public health hazards and enrich communication strategies and proactive actions in public health issues and opinion management during the COVID-19 pandemic.

How Scientists View Vaccine Hesitancy

This paper examines possible causes, consequences, and potential solutions for addressing vaccine hesitancy in the United States, focusing on the perspectives of academic scientists. By examining the experiences of scientists, who are arguably a critical community in US society, we gain deeper insights into how they understand the complexities of vaccine hesitancy and whether their insights and opinions converge with or diverge from the current literature. We present findings from a national survey of a representative sample of academic scientists from the fields of biology and public health regarding vaccine hesitancy and related topics. Empirical analysis using descriptive, bivariate, and multivariate analyses covers multiple topics, including vaccine controversy, trust in science, causes of vaccine hesitancy, preferred policy and regulatory approaches, risk perceptions, and scientists' ethics and perceived communication roles. The results highlight a diversity of opinions within the scientific community regarding how to improve science-society communication in regard to vaccines, including the need to be transparent and candid to the public about the risk of vaccines and their research.

Theoretical and practical aspects of risk communication in food safety: A review study

Currently, food safety hazards have introduced as one of the most important threats to public health worldwide. Considering numerous crises in the field of food safety at global, regional, and national levels, and their impact on the physical and mental health of consumers, it is very vital to evaluate risk communication strategies in each country. Food safety risk communication (FSRC) aims to provide the means for individuals to protect their health from food safety risks and make informed decisions about food risks. The purpose of this study is to present FSRC as one of the key parts of risk analysis, its importance considering the prevalence of food contamination and recent crises related to food. Additionally, the stages of implementation of FSRC are mentioned. In FSRC, it is essential to comply with the principles and prerequisites. There are various strategies for FSRC nowadays. Different platforms for FSRC are rapidly evolving. Choosing and evaluating the appropriate strategy according to the target group, consensus of stakeholders, cooperation and coordination of risk assessors and risk managers have a significant impact in order to improve and implement FSRC.

Dialogic communication on local government social media during the first wave of COVID-19: Evidence from the health commissions of prefecture-level cities in China

Although some scholars have explored the level and determinants of Dialogic Communication on Government Social Media (DCGSM), none have conducted their studies in the context of public crisis. The current study contributes to the understanding on DCGSM by 16,822 posts crawled from the official Sina Weibo accounts of 104 Chinese health commissions in prefecture-level cities during the first wave of the COVID-19 pandemic. Results show that Chinese local government agencies have great variations in their DCGSM during the pandemic and the overall performance is poor. Furthermore, Chinese local governments prefer to conserve visitors and generate return visits, rather than dialogic loops development and the usefulness of information enhancement. The findings suggest that both public pressure and peer pressure contribute to the DCGSM of Chinese local governments during the public health crisis. In addition, the effect of public pressure is stronger than that of the peer pressure, indicating that local government agencies have experienced more demand-pull DCGSM.

Lessons Learned from a Global Perspective of Coronavirus Disease-2019

Coronavirus disease-2019 has impacted the world globally. Countries and health care organizations across the globe responded to this unprecedented public health crisis in a varied manner in terms of public health and social measures, vaccination development and rollout, the conduct of research, developments of therapeutics, sharing of information, and in how they continue to deal with the widespread aftermath. This article reviews the various elements of the global response to the pandemic, focusing on the lessons learned and strategies to consider during future pandemics.

Information under lockdown: A content analysis of government communication strategies on Facebook during the COVID-19 outbreak

The aim of this study is to investigate how central government agencies used social media to communicate and disseminate information to the public during the Coronavirus outbreak. In addition, this study seeks to examine the characteristics of the messages, content, and engagement rates of the information which has been published by the four central government bodies responsible for the management of the emerging crisis in Israel. This article is based on content analysis to examine the work of four main government ministries on Facebook (Ministry of Health, Ministry of Defense, Ministry of Education and Ministry of Finance) throughout the first six months of the crisis from February to July 2020. Findings indicate that The Ministry of Health's posts yielded the highest engagement rates compared to the rest of the ministries. Also, we categorized the posts into four main categories: Policy, Advocacy & COVID-19 additional information, Restrictions, Guidelines & Recommendations. In terms of Sentiment analysis, posts containing restrictions have created the highest emotional reactions (positive and negative). Research findings can be deduced regarding modes of distribution in terms of messages, publication dates, and types of content to improve users' responses in terms of audience engagement and sentiment.

Communicating COVID-19 Risk on Instagram: A Content Analysis of Official Public Health Messaging During the First Year of the Pandemic

Early in the COVID-19 pandemic, social media platform Instagram surged in popularity as a source of health information. Both the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) leveraged Instagram accounts to publicly distribute COVID-related information. The current study investigated whether WHO and CDC messaging strategies on Instagram adhered to best practices defined by two theoretical frameworks: the extended parallel process model and crisis and emergency risk communication. We conducted a quantitative content analysis of COVID-related posts (n = 726) published between January-December 2020 to determine how both agencies (1) communicated the threat of the pandemic (e.g. susceptibility and severity of negative COVID-19 consequences); (2) appealed to self-, response, and collective efficacy; (3) incorporated cues to action (e.g. preventive behaviors, information seeking); and (4) leveraged credibility cues (e.g. scientific evidence, experts). Results showed threat information was limited, whereas efficacy appeals and cues to action were abundant. The CDC relied more heavily on depictions of self- and response efficacy, whereas the WHO appealed more frequently than the CDC to collective efficacy. Neither visually modeled behaviors nor leveraged scientific evidence or experts with great frequency. Implications for future research and official communication efforts via social media are discussed.

What message features influence the intention to share misinformation about COVID-19 on social media? The role of efficacy and novelty

Given the amount of misinformation being circulated on social media during the COVID-19 pandemic and its potential threat to public health, it is imperative to investigate ways to hinder its transmission. To this end, this study aimed to identify message features that may contribute to misinformation sharing on social media. Based on the theory of social sharing of emotion and the extant research on message credibility, this study examined if emotions and message credibility serve as mechanisms through which novelty and efficacy of misinformation influence sharing intention. An online experiment concerning COVID-19 misinformation was conducted by employing a 2 (novelty conditions: high vs. low) × 2 (efficacy conditions: high vs. low) between-subjects design using a national quota sample in South Korea (N = 1,012). The findings suggested that, contrary to the expectation, the overall effects of novelty on sharing intention were negative. The specific mechanisms played significant and unique roles in different directions: novelty increased sharing intention by evoking surprise, while also exerting a negative influence on sharing intention through an increase in negative emotions and a decrease in positive emotions and message credibility. Consistent with the expectation, efficacy exhibited positive total effects on sharing intention, which was explained by higher levels of (self- and response-) efficacy of protective action increasing positive emotions and message credibility but decreasing negative emotions. The implications and limitations of the study are discussed.

Crisis communication in the WHO COVID-19 press conferences: A retrospective analysis

OBJECTIVES

The objective of this study is to investigate, from a longitudinal perspective, how WHO communicated COVID-19 related information to the public through its press conferences during the first two years of the pandemic.

METHODS

The transcripts of 195 WHO COVID-19 press conferences held between January 22, 2020 and February 23, 2022 were collected. All transcripts were syntactically parsed to extract highly frequent noun chunks that were potential topics of the press conferences. First-order autoregression models were fit to identify "hot" and "cold" topics. In addition, sentiments and emotions expressed in the transcripts were analyzed using lexicon-based sentiment/emotion analyses. Mann-Kendall tests were performed to capture the possible trends of sentiments and emotions over time.

RESULTS

First, eleven "hot" topics were identified. These topics were pertinent to anti-pandemic measures, disease surveillance and development, and vaccine-related issues. Second, no significant trend was captured in sentiments. Last, significant downward trends were found in anticipation, surprise, anger, disgust, and fear. However, no significant trends were found in joy, trust, and sadness.

CONCLUSIONS

This retrospective study provided new empirical evidence on how WHO communicated issues pertaining to COVID-19 to the general public through its press conferences. With the help of the study, members of the general public, health organizations, and other stake-holders will be able to better understand the way in which WHO has responded to various critical events during the first two years of the pandemic.

Governance in mental healthcare policies during the COVID-19 pandemic in Mexico

The COVID-19 pandemic has become the greatest burden of disease worldwide and in Mexico, affecting more vulnerable groups in society, such as people with mental disorders (MD). This research aims to analyze the governance processes in the formulation of healthcare policies for people with MD in the face of the COVID-19 pandemic. An analytical qualitative study, based on semi-structured interviews with key informants in the healthcare system was conducted in 2020. The study followed the theoretical-methodological principles of the Governance Analytical Framework (GAF). The software ATLAS.ti-V.9 was used for inductive thematic analysis, classifying themes and their categories. To ensure the proper interpretation of the data, a process of triangulation among the researchers was carried out. The findings revealed that in Mexico, the federal Secretary of Health issued guidelines for mental healthcare, but there is no defined national policy. Decision-making involved multiple actors, with different strategies and scopes, depending on the type of key-actor and their level of influence. Majority of informants described a problem of implementation in which infection control policies in the psychiatric population were the same as in the general populations which decreased the percentage of access to healthcare during the pandemic, without specific measures to address this vulnerable population. The results suggest that there is a lack of specific policies and measures to address the needs of people with mental disorders during the COVID-19 pandemic in Mexico. It also highlights the importance of considering the role of different actors and their level of influence in the decision-making process.

Exploring customer concerns on service quality under the COVID-19 crisis: A social media analytics study from the retail industry

The COVID-19 pandemic has triggered a set of government policies and supermarket regulations, which affects customers' grocery shopping behaviours. However, the specific impact of COVID-19 on retailers at the customer end has not yet been addressed. Using text-mining techniques (i.e., sentiment analysis, topic modelling) and time series analysis, we analyse 161,921 tweets from leading UK supermarkets during the first COVID-19 lockdown. The results show the causes of sentiment change in each time series and how customer perception changes according to supermarkets’ response actions. Drawing on the social media crisis communication framework and Situational Crisis Communication theory, this study investigates whether responding to a crisis helps retail managers better understand their customers. The results uncover that customers experiencing certain social media interactions may evaluate attributes differently, resulting in varying levels of customer information collection, and grocery companies could benefit from engaging in social media crisis communication with customers. As new variants of COVID-19 keep appearing, emerging managerial problems put businesses at risk for the next crisis. Based on the results of text-mining analysis of consumer perceptions, this study identifies emerging topics in the UK grocery sector in the context of COVID-19 crisis communication and develop the sub-dimensions of service quality assessment into four categories: physical aspects, reliability, personal interaction, and policies. This study reveals how supermarkets could use social media data to better analyse customer behaviour during a pandemic and sustain competitiveness by upgrading their crisis strategies and service provision. It also sheds light on how future researchers can leverage the power of social media data with multiple text-mining methodologies.

Service failures in times of crisis: An analysis of eWOM emotionality

The COVID-19 pandemic continues to disrupt consumer experiences as well as service operations. Despite the magnitude of this exogenous shock, little is known about the pandemic's impact on consumers. Building on engagement theory, this study examines consumers' emotional responses to service failures on social media. Contributing to the brand equity literature, we test whether electronic word-of-mouth (eWOM) emotionality is contingent on brand strength. To do so, we analyzed 327,205 tweets directed at airline brands over the first 12 months of the pandemic in addition to data from a nonaffected period. The models show that consumers' overall emotionality in tweets was lower during the pandemic than before it. Over the course of the pandemic, levels of joy were lower while levels of sadness and anger were more prominent in tweets directed at weaker brands. Thus, brand strength still acts as a "buffer" if service failures are caused by exogenous shocks.

Predicting social media rumours in the context of public health emergencies

The spread of rumours on social media in the context of public health emergencies often distorts perceptions of public events and obstructs crisis management. Microblog entries about 28 rumour cases are collected on Sina Weibo during the COVID-19 outbreak. The Modality–Agency–Interactivity–Navigability model is used to identify the key factors of rumour prediction. To investigate the relationship among information modality, information content, information source and rumour identification, the binary logistic regression model is established based on the features of users and microblog entries. In addition, we propose a multi-feature rumour prediction model based on the Bidirectional Encoder Representations from Transformers (BERT) and Extreme Gradient Boosting (XGBoost) models. The proposed rumour prediction model has the best performance compared with other models. The feature importance is then calculated by the SHapley Additive exPlanations (SHAP), which can also explain the XGBoost results. It is shown that the likelihood that microblog entries are rumours decreases as the values of variables such as user influence and the positive sentiment of comments rise. Microblog entries posted on Thursdays or at noon are more probably to be rumours than those posted at other time. The proposed model can assist emergency management departments in establishing a feasible rumour prediction mechanism to guide public opinion against rumours.

COVID-19 in South Carolina: Experiences Using Facebook as a Self-Organizing Tool for Grassroots Advocacy, Education, and Social Support

This retrospective case study describes our experiences, processes, and lessons learned using social media for pandemic response. Our team created and maintained a large Facebook group, and we used this platform to support grassroots advocacy, public health messaging, and health equity during the COVID-19 pandemic in South Carolina. The Facebook group was initially formed to urge local and state leaders to implement a stay-at-home order, but we recognized a continued need for our virtual space. Group leaders performed tasks including data tracking/reporting and content review/approval. Initial advocacy successes included the stay-at-home order, efforts to limit transmission, and social/mental health support. As the Delta variant emerged, we posted vaccine education and access information and supported school mitigation, including a successful litigation effort that led to a mask requirement on school buses. With the Omicron variant, our group’s focus shifted to educating about immune evasion, transmissibility, and individual protection. This included updates on mask use, antigen testing, vaccine boosters, treatment, data reports, and vaccines. Throughout the pandemic, we addressed health equity, especially for those identifying as disabled. We learned that virtual communities could support each other and improve public health, even when disinformation was present and elected officials emphasized politics over science.

An easy numeric data augmentation method for early-stage COVID-19 tweets exploration of participatory dynamics of public attention and news coverage

With the onset of COVID-19, the pandemic has aroused huge discussions on social media like Twitter, followed by many social media analyses concerning it. Despite such an abundance of studies, however, little work has been done on reactions from the public and officials on social networks and their associations, especially during the early outbreak stage. In this paper, a total of 9,259,861 COVID-19-related English tweets published from 31 December 2019 to 11 March 2020 are accumulated for exploring the participatory dynamics of public attention and news coverage during the early stage of the pandemic. An easy numeric data augmentation (ENDA) technique is proposed for generating new samples while preserving label validity. It attains superior performance on text classification tasks with deep models (BERT) than an easier data augmentation method. To demonstrate the efficacy of ENDA further, experiments and ablation studies have also been implemented on other benchmark datasets. The classification results of COVID-19 tweets show tweets peaks trigged by momentous events and a strong positive correlation between the daily number of personal narratives and news reports. We argue that there were three periods divided by the turning points on January 20 and February 23 and the low level of news coverage suggests the missed windows for government response in early January and February. Our study not only contributes to a deeper understanding of the dynamic patterns and relationships of public attention and news coverage on social media during the pandemic but also sheds light on early emergency management and government response on social media during global health crises.

Analysis of government agencies and stakeholders’ twitter communications during the first surge of COVID-19 in Brazil

BACKGROUND: Official authorities are in charge of communicating with the public in a consistent and coherent manner. The impact of social media on managing the coronavirus 2019 (COVID-19) pandemic potentially influenced social behavior in Brazil. OBJECTIVE: Using Twitter, this study analyzes communications about the COVID-19 pandemic from official agencies of the Brazilian government and key public sector decision-makers. METHOD: We captured public Twitter messages about COVID-19 exchanged between authorities at the federal, state, and municipal levels of government. These messages were further classified into guidance and information messages or disinformation messages. Finally, through analysis of tweets and their frequency, we evidenced the level of information generated by the three levels of government. RESULTS: Our analyses show an underestimation of the magnitude of the pandemic by Brazilian government authorities. None of the spheres of government anticipated the imminent health crisis, did not issue good recommendations and guidelines, and did not take preventive actions. CONCLUSION: The lack of governmental actions and adequate guidance in Brazil has led to an explosive increase in infected people and deaths. Surprisingly, this was not due to technical or structural reasons. It resulted from conflicting communication strategies implemented by the federal, state, and municipal governments in attempts to minimize the effects of COVID-19 on their local health structures.

An SEM-ANN approach to evaluate public awareness about COVID, A pathway toward adaptation effective strategies for sustainable development

This study was conducted to evaluate public awareness about COVID with aimed to check public strategies against COVID-19. A semi structured questionnaire was collected and the data was analyzed using some statistical tools (PLS-SEM) and artificial neural networks (ANN). We started by looking at the known causal linkages between the different variables to see if they matched up with the hypotheses that had been proposed. Next, for this reason, we ran a 5,000-sample bootstrapping test to assess how strongly our findings corroborated the null hypothesis. PLS-SEM direct path analysis revealed HRP -> PA-COVID, HI -> PA-COVID, MU -> PA-COVID, PM -> PA-COVID, SD -> PA-COVID. These findings provide credence to the acceptance of hypotheses H1, H3, and H5, but reject hypothesis H2. We have also examined control factors such as respondents' age, gender, and level of education. Age was found to have a positive correlation with PA-COVID, while mean gender and education level were found to not correlate at all with PA-COVID. However, age can be a useful control variable, as a more seasoned individual is likely to have a better understanding of COVID and its effects on independent variables. Study results revealed a small moderation effect in the relationships between understudy independent and dependent variables. Education significantly moderates the relationship of PA-COVID associated with MU, PH, SD, RP, PM, PA-COVID, depicts the moderation role of education on the relationship between MU*Education->PA-COVID, HI*Education->PA.COVID, SD*Education->PA.COVID, HRP*Education->PA.COVID, PM*Education -> PA.COVID. The artificial neural network (ANN) model we've developed for spreading information about COVID-19 (PA-COVID) follows in the footsteps of previous studies. The root means the square of the errors (RMSE). Validity measures how well a model can predict a certain result. With RMSE values of 0.424 for training and 0.394 for testing, we observed that our ANN model for public awareness of COVID-19 (PA-COVID) had a strong predictive ability. Based on the sensitivity analysis results, we determined that PA. COVID had the highest relative normalized relevance for our sample (100%). These factors were then followed by MU (54.6%), HI (11.1%), SD (100.0%), HRP (28.5%), and PM (64.6%) were likewise shown to be the least important factors for consumers in developing countries struggling with diseases caused by contaminated water. In addition, a specific approach was used to construct a goodness-of-fit coefficient to evaluate the performance of the ANN models. The study will aid in the implementation of effective monitoring and public policies to promote the health of local people.

Opinion analysis and aspect understanding during covid-19 pandemic using BERT-Bi-LSTM ensemble method

Social media platforms significantly increase general information about disease severity and inform preventive measures among community members. To identify public opinion through tweets on the subject of Covid-19 and investigate public sentiment in the country over the period. This article proposed a novel method for sentiment analysis of coronavirus-related tweets using bidirectional encoder representations from transformers (BERT) bi-directional long short-term memory (Bi-LSTM) ensemble learning model. The proposed approach consists of two stages. In the first stage, the BERT model gains the domain knowledge with Covid-19 data and fine-tunes with sentiment word dictionary. The second stage is the Bi-LSTM model, which is used to process the data in a bi-directional way with context sequence dependency preserving to process the data and classify the sentiment. Finally, the ensemble technique combines both models to classify the sentiment into positive and negative categories. The result obtained by the proposed method is better than the state-of-the-art methods. Moreover, the proposed model efficiently understands the public opinion on the Twitter platform, which can aid in formulating, monitoring and regulating public health policies during a pandemic.

Agenda-Setting for COVID-19: A Study of Large-Scale Economic News Coverage Using Natural Language Processing

Over the past two years, organizations and businesses have been forced to constantly adapt and develop effective responses to the challenges of the COVID-19 pandemic. The acuteness, global scale and intense dynamism of the situation make online news and information even more important for making informed management and policy decisions. This paper focuses on the economic impact of the COVID-19 pandemic, using natural language processing (NLP) techniques to examine the news media as the main source of information and agenda-setters of public discourse over an eight-month period. The aim of this study is to understand which economic topics news media focused on alongside the dominant health coverage, which topics did not surface, and how these topics influenced each other and evolved over time and space. To this end, we used an extensive open-source dataset of over 350,000 media articles on non-medical aspects of COVID-19 retrieved from over 60 top-tier business blogs and news sites. We referred to the World Economic Forum's Strategic Intelligence taxonomy to categorize the articles into a variety of topics. In doing so, we found that in the early days of COVID-19, the news media focused predominantly on reporting new cases, which tended to overshadow other topics, such as the economic impact of the virus. Different independent news sources reported on the same topics, showing a herd behavior of the news media during this global health crisis. However, a temporal analysis of news distribution in relation to its geographic focus showed that the rise in COVID-19 cases was associated with an increase in media coverage of relevant socio-economic topics. This research helps prepare for the prevention of social and economic crises when decision-makers closely monitor news coverage of viruses and related topics in other parts of the world. Thus, monitoring the news landscape on a global scale can support decision-making in social and economic crises. Our analyses point to ways in which this monitoring and issues management can be improved to remain alert to social dynamics and market changes.

Dealing with the COVID-19 crisis: Theoretical application of social media analytics in government crisis management

Little theory-grounded research addresses how to use social media strategically in government public relations through machine learning. To fill this gap, we propose a way to optimize social media analytics to manage issues and crises by using the framework of attribution theory to analyze 360,861 tweets. In particular, we examined the attribution of crisis responsibility related to the spread of COVID-19 and its relations to the negative emotions of U.S. citizens on Twitter for six months (from January 20 to June 30, 2020). The results of this study showed that social media analytics is a valid tool to monitor how the spread of COVID-19 evolved from an issue to a crisis for the Trump administration. In addition, the federal government's lack of response and inability to handle the outbreak led to citizens' engagement and amplification of negative tweets that blamed the Trump White House. Theoretical and practical implications of the results are discussed.

Social media mining under the COVID-19 context: Progress, challenges, and opportunities

Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.

Understanding the Scientific Topics in the Chinese Government’s Communication about COVID-19: An LDA Approach

The communication of scientific topics can play a key role in the fight against misinformation and has become an important component of governments’ communication regarding COVID-19. This study reviewed the Chinese government’s COVID-19 information sources and identified the patterns of science communication models within them. A corpus of science-related content was collected and coded from 1521 news briefings announced by the Chinese government. An LDA (latent Dirichlet allocation) topic model, correlation analysis, and ANOVA were used to analyze the framing of the scientific topics and their social environmental characteristics. The major findings showed the following: (1) The frames in the Chinese government’s communication of scientific topics about COVID-19 had three purposes—to disseminate knowledge about prevention and control, epidemiological investigations, and the public’s personal health; to make the public understand scientific R&D in Chinese medicine, enterprises, vaccines, treatment options, and medical resources; and to involve citizens, communities, and enterprises in scientific decision making. (2) The frames were correlated with the public and media concerns. (3) The frames varied with the different levels of officials, different types of government agencies, different income regional governments, and different severity levels of the epidemic. (4) The topics concerning sustainability science were more correlated with public and media concern. In addition, we propose several suggestions for building sustainable communication approaches during the pandemic.

Visualizing Social Media Research in the Age of COVID-19

During the last three years, numerous research papers have been reported which use social media data to explore several issues related to the COVID-19 pandemic. Bibliometric methods in this work are used to analyze 1427 peer-reviewed documents from the last three years extracted from the Web of Science database. The results of this study show that there was high growth in publications in open access journals with an annual rate reaching 19.3% and they also identify the top cited journals and research papers. The thematic analysis of papers shows that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, mental health, misinformation, and fake news are important and well-developed, whereas topics related to distance-learning education with social media are emerging. The results also show that the USA, China, and the UK have published many papers and received a high number of citations because of their strong international collaboration.

Barely Tweeting and Rarely About Racism: Assessing US State Health Department Twitter Use During the COVID-19 Vaccine Rollout

Introduction

The general public was discussing racism and potential inequities in COVID-19 vaccinations among African Americans on Twitter before the first COVID-19 vaccine received emergency use authorization, but it is unclear how US state health departments (SHDs) were using Twitter to address the inequities. This study examines the frequency, content and timing of SHD tweets during the US rollout of the first SARS Co-V2 vaccine.

Methods

This was a prospective study of tweets posted from the official Twitter accounts of each of the 50 US SHDs and the DC health department from October 19, 2020 to February 28, 2021. We retrieved the content and metadata of 100% of their tweets; calculated frequencies and proportions of tweets containing key terms related to COVID-19 vaccines, equity and racism; stratified the data by region; and charted longitudinal trends.

Results

Overall, SHDs tweeted infrequently, and rarely tweeted about inequities, mistrust or racism. Though 55.48% of all SHD tweets were about COVID-19, hardly any tweets contained the terms: race/ethnicity (1.20%); equity (1.09); mistrust (.59%); or racism (.06%). Similar patterns existed among vaccination-related tweets, which accounted for 24.38% of all tweets. Only 21.64% of vaccination-related tweets containing any race/ethnicity, equity, mistrust, or racism terms were posted prior to the first Emergency Use Authorization (EUA). Those about African Americans (70.45%) were posted ≥8 weeks after EUA.

Conclusions

Concerns about racism and inequities in COVID-19 vaccination continue on Twitter, but SHDs rarely tweet about them. This strikes a worrisome chord of disconnection from the science linking health inequities to racism.

Platform Effects on Public Health Communication: A Comparative and National Study of Message Design and Audience Engagement Across Twitter and Facebook

BACKGROUND

Public health agencies widely adopt social media for health and risk communication. Moreover, different platforms have different affordances, which may impact the quality and nature of the messaging and how the public engages with the content. However, these platform effects are not often compared in studies of health and risk communication and not previously for the COVID-19 pandemic.

OBJECTIVE

This study measures the potential media effects of Twitter and Facebook on public health message design and engagement by comparing message elements and audience engagement in COVID-19-related posts by local, state, and federal public health agencies in the United States during the pandemic, to advance theories of public health messaging on social media and provide recommendations for tailored social media communication strategies.

METHODS

We retrieved all COVID-19-related posts from major US federal agencies related to health and infectious disease, all major state public health agencies, and selected local public health departments on Twitter and Facebook. A total of 100,785 posts related to COVID-19, from 179 different accounts of 96 agencies, were retrieved for the entire year of 2020. We adopted a framework of social media message elements to analyze the posts across Facebook and Twitter. For manual content analysis, we subsampled 1677 posts. We calculated the prevalence of various message elements across the platforms and assessed the statistical significance of differences. We also calculated and assessed the association between message elements with normalized measures of shares and likes for both Facebook and Twitter.

RESULTS

Distributions of message elements were largely similar across both sites. However, political figures (P<.001), experts (P=.01), and nonpolitical personalities (P=.01) were significantly more present on Facebook posts compared to Twitter. Infographics (P<.001), surveillance information (P<.001), and certain multimedia elements (eg, hyperlinks, P<.001) were more prevalent on Twitter. In general, Facebook posts received more (normalized) likes (0.19%) and (normalized) shares (0.22%) compared to Twitter likes (0.08%) and shares (0.05%). Elements with greater engagement on Facebook included expressives and collectives, whereas posts related to policy were more engaged with on Twitter. Science information (eg, scientific explanations) comprised 8.5% (73/851) of Facebook and 9.4% (78/826) of Twitter posts. Correctives of misinformation only appeared in 1.2% (11/851) of Facebook and 1.4% (12/826) of Twitter posts.

CONCLUSIONS

In general, we find a data and policy orientation for Twitter messages and users and a local and personal orientation for Facebook, although also many similarities across platforms. Message elements that impact engagement are similar across platforms but with some notable distinctions. This study provides novel evidence for differences in COVID-19 public health messaging across social media sites, advancing knowledge of public health communication on social media and recommendations for health and risk communication strategies on these online platforms.

Attitudes towards urban green during the COVID-19 pandemic via Twitter

COVID-19 has had economic, social and environmental impacts worldwide. Governments have adopted containment measures to limit the spread of the virus. Urban green spaces (UGSs) were included among the non-essential activities and were consequently closed during the lockdown periods in some countries. This study analysed tweets posted by users to understand the citizens' perception and sentiment in relation to the closure of UGS in Italy. Results revealed that people felt a strong deprivation feeling in relation to the restrictions imposed on UGS access, which limited the number of spaces for supporting mental and physical wellbeing of citizens. Users from urban areas were more affected by the lockdowns and more willing to share thoughts on social media, demonstrating a strong emotionality. Furthermore, findings show that users seemed concerned about their children's health, expressing awareness about the benefits of being in contact with nature. UGS is able to provide services to citizens, and close-to-home parks are fundamental for the community, in particular during a health emergency. The implementation of urban design, which includes green areas to support health and environment challenges, should be addressed by policy-makers to create opportunities for a green and resilient recovery of cities, and prepare for future emergencies.

Global and Local Trends Affecting the Experience of US and UK Healthcare Professionals during COVID-19: Twitter Text Analysis

Background: Healthcare professionals (HCPs) are on the frontline of fighting the COVID-19 pandemic. Recent reports have indicated that, in addition to facing an increased risk of being infected by the virus, HCPs face an increased risk of suffering from emotional difficulties associated with the pandemic. Therefore, understanding HCPs’ experiences and emotional displays during emergencies is a critical aspect of increasing the surge capacity of communities and nations. Methods: In this study, we analyzed posts published by HCPs on Twitter to infer the content of discourse and emotions of the HCPs in the United States (US) and United Kingdom (UK), before and during the COVID-19 pandemic. The tweets of 25,207 users were analyzed using natural language processing (NLP). Results: Our results indicate that HCPs in the two countries experienced common health, social, and political issues related to the pandemic, reflected in their discussion topics, sentiments, and emotional display. However, the experiences of HCPs in the two countries are also subject to local socio-political trends, as well as cultural norms regarding emotional display. Conclusions: Our results support the potential of utilizing Twitter discourse to monitor and predict public health responses in emergencies.

Government dissemination of epidemic information as a policy instrument during COVID-19 pandemic: Evidence from Chinese cities

COVID-19 has given rise to a surge in the number of policy instruments used to deal with the pandemic at different levels of governments globally. While much attention has been placed on travel bans, lockdown, social distancing, and economic stimulus packages, government dissemination of epidemic information as a policy instrument has received less attention. Based on 14,637 news items collected from the portals of 79 municipal governments in China, this study aims to 1) conduct a content analysis of news items and construct three key attributes of governments' practices of epidemic information dissemination, namely, comprehensiveness, responsiveness, and the protection of privacy, and 2) study the patterns and determinants of the dissemination of epidemic information. Our results show that these cities vary substantially in how they disseminate statistical data and information on individual cases of COVID-19 infections within their localities, which are shaped by government performance in open data, severity of the pandemic, cities' administrative level, population, and health sector capacities. The findings generate theoretical and policy implications for government dissemination of epidemic information.

The psychological reassurance effect of mobile tracing apps in Covid-19 Era

As part of their public health policies, most countries have launched mobile tracing applications (apps) to reduce the spread of the COVID-19 virus and reassure their citizens. To the best of our knowledge, no study has explored the importance of 'well-being' and 'trust in the future' in the context of digital contact-tracing apps. This is an important gap, especially given the importance of citizens' acceptance of a mobile tracing app and its role in reassuring citizens. Therefore, we study the French government's tracing app-StopCovid-as experienced by a sample of 832 participants from France. The results establish strong links between perceived value and trust in government, well-being, and trust in the future, which are considered the key features of the reassurance effect in a pandemic context. In addition, a multigroup analysis (MGA) allows us to compare the effect of several moderators on the overall model, such as the users versus nonusers of tracking apps or infected versus noninfected with COVID-19. The study provides practical implications by highlighting how governments should deploy mobile tracing apps to contribute to public health and reassure their citizens during the pandemic.

Online information and support seeking during COVID-19 lockdown in Wuhan: implications for health promotion

The lockdown that was deployed in Wuhan, China to combat the COVID-19 pandemic curbed the infection but also created great information challenges for people in social isolation. This resulted in surge in online health information seeking (OHIS) behaviors of the patients and their families. While the Internet has been widely used by Chinese public to access and search health information, there is relatively little research in the context of pandemic outbreaks, especially at the onset of a strong lockdown while many people were panicking. From a total of 10 908 ‘#COVID-19 Patient Seeking Help’ posts on Weibo in a period of 20 days when the lockdown policy was first initiated, we identified 1496 unique patients living in or with family in Wuhan, China. Using textual analysis, we explored OHIS behaviors at the onset of the pandemic. Many faced increased difficulties accessing offline healthcare services and such turned to social media for help and information. In particular, the findings highlight the following themes: ‘OHIS for medical treatment’, ‘OHIS to manage self-quarantine’, ‘OHIS for tangible support’ and ‘OHIS to navigate information discrepancy’. Overall, our findings provide important insights into health information seeking behaviors and the role of social media during a pandemic. Our findings also highlight the importance of considering people’s information need and challenges created due to the lockdown policies in the future pandemic communication and preparedness.

Do They Really Work? Quantifying Fabric Mask Effectiveness to Improve Public Health Messaging

The purpose of this study is to compare masks (non-medical/fabric, surgical, and N95 respirators) on filtration efficiency, differential pressure, and leakage with the goal of providing evidence to improve public health messaging. Masks were tested on an anthropometric face filtration mount, comparing both sealed and unsealed. Overall, surgical and N95 respirators provided significantly higher filtration efficiency (FE) and differential pressure (dP). Leakage comparisons are one of the most significant factors in mask efficiency. Higher weight and thicker fabric masks had significantly higher filtration efficiency. The findings of this study have important implications for communication and education regarding the use of masks to prevent the spread of COVID-19 and other respiratory illnesses, specifically the differences between sealed and unsealed masks. The type and fabric of facial masks and whether a mask is sealed or unsealed has a significant impact on the effectiveness of a mask. Findings related to differences between sealed and unsealed masks are of critical importance for health care workers. If a mask is not completely sealed around the edges of the wearer, FE for this personal protective equipment is misrepresented and may create a false sense of security. These results can inform efforts to educate health care workers and the public on the importance of proper mask fit.

Information sharing practices during the COVID-19 pandemic: A case study about face masks

This article contributes an empirical analysis of information sharing practices on Twitter relating to the use of face masks in the context of COVID-19. Behavioural changes, such as the use of face masks, are often influenced by people's knowledge and perceptions, which in turn can be affected by the information available to them. Face masks were not recommended for use by the UK public at the beginning of the COVID-19 pandemic. Due to developments in scientific understanding, the guidance changed and by the end of 2020 they were mandatory on public transport and in shops. This research examines tweets in this longitudinal context and, therefore, provides novel insights into the dynamics of crisis communication in an ongoing crisis event with emerging scientific evidence. Specifically, analysis of the content of tweets, external resources most frequently shared, and users sharing information are considered. The conclusions contribute to developing understanding of the digital information ecology and provide practical insights for crisis communicators. Firstly, the analysis shows changes in the frequency of tweets about the topic correspond with key guidance and policy changes. These are, therefore, points in time official channels of information need to utilise the public's information seeking and sharing practices. Secondly, due to changes in face mask guidance and policy, the current literature on digital information ecology is insufficient for capturing the dynamic nature of a long-term ongoing crisis event. Challenges can arise due to the prolonged circulation of out-of-date information, i.e. not strategic misinformation, nor "mis"-information at all, which can have serious ramifications for crisis communication practitioners. Thirdly, the role of traditional media and other journalism/broadcasting platforms in shaping conversations is evident, as is the potential for scientific organisations' and individual people's Twitter user accounts. This plurality of contributors needs to be acknowledged and understood to inform crisis communication strategies.

Pandemic Experience of First Responders: Fear, Frustration, and Stress

Police officers, firefighters, and paramedics are on the front lines of crises and emergencies, placing them at high risk of COVID-19 infection. A deeper understanding of the challenges facing first responders during the COVID-19 pandemic is necessary to better support this important workforce. We conducted semi-structured interviews with 21 first responders during the COVID-19 pandemic, asking about the impact of COVID-19. Data collected from our study interviews revealed that, despite large numbers of COVID-19 infections among the staff of police and fire departments, some—but not all—first responders were concerned about COVID-19. A similar divide existed within this group regarding whether or not to receive a COVID-19 vaccination. Many first responders reported frustration over COVID-19 information because of inconsistencies across sources, misinformation on social media, and the impact of politics. In addition, first responders described increased stress due to the COVID-19 pandemic caused by factors such as the fear of COVID exposure during emergency responses, concerns about infecting family members, and frustration surrounding new work policies. Our findings provide insight into the impact of COVID-19 on first responders and highlight the importance of providing resources for education about COVID-19 risks and vaccination, as well as for addressing first responders’ mental health and well-being.

Effects of local government social media use on citizen compliance during a crisis: Evidence from the COVID-19 crisis in China

Improving citizen compliance is a major goal of public administration, especially during crises. Although social media are widely used by government agencies across the globe, it is still unclear that whether the use of social media can help local governments improve citizen compliance especially during crises. Based on an original daily panel dataset of 189 cities in China during COVID-19, this study provides empirical evidence for the positive effect that crisis-related social media posts published by local government agencies has on citizen compliance. In addition, this effect is mediated by the topic of prevention measures in social media posts, and is stronger in cities with higher GDP per capita, better educated citizens and wider internet coverage. The findings imply that social media is an efficient and low-cost tool to assist local government agencies to achieve public administration objectives during crises, and its efficacy is largely dependent on regional socioeconomic status.

COVID-19 concerns in cyberspace predict human reduced dispersal in the real world: Meta-regression analysis of time series relationships across American states and 115 countries/territories

On the basis of parasite-stress theory of sociality and behavioral immune system theory, this research examined how concerns regarding the Coronavirus disease 2019 (COVID-19) in cyberspace (i.e., online search volume for coronavirus-related keywords) would predict human reduced dispersal in the real world (i.e., human mobility trends throughout the pandemic) between January 05, 2020 and May 22, 2021. Multiple regression analyses controlling for COVID-19 cases per million, case fatality rate, death-thought accessibility, government stringency index, yearly trends, season, religious holidays, and reduced dispersal in the preceding week were conducted. Meta-regression analysis of the multiple regression results showed that when there were high levels of COVID-19 concerns in cyberspace in a given week, the amount of time people spent at home increased from the previous week across American states (Study 1) and 115 countries/territories (Study 2). Across studies, the associations between COVID-19 concerns and reduced dispersal were stronger in areas of higher historical risks of infectious-disease contagion. Compared with actual coronavirus threat, COVID-19 concerns in cyberspace had significantly larger effects on predicting human reduced dispersal in the real world. Thus, online query data have invaluable implications for predicting large-scale behavioral changes in response to life-threatening events in the real world and are indispensable for COVID-19 surveillance.

Relevance of E-Participation in the state health campaign in Spain: #EstoNoEsUnJuego / #ThisIsNotAGame

Confronting the COVID-19 health emergency has forced public administrations in Spain to work with various networks as a means of promoting their campaigns to citizens. This paper aims to analyse digital citizens' e-participation by focusing on the state health campaign #EstoNoEsUnJuego - #ThisIsNotAGame. This campaign was launched by the Spanish Ministry of Health in September 2020 via Twitter with the objective of reinforcing protection measures against the virus. A sample consisting of 19,576 tweets, sent from September 2020 to February 2021, was investigated and the results have indicated that, of 9133 users, 64.8% of citizens collaborated in the dissemination of tweets. It was observed that most messages supported the campaign by disseminating information on measures, data and news. Only 0.1% of the messages were aggressive. The conclusion is that, despite not having created a true form of communication between public institutions and citizens, e-participation has generated a functional connection between them. Citizens have acquired a responsible and participatory digital role which, although failing to show personal involvement in their comments, has been the main driving force behind the success of this campaign.

Emotions and emotion up-regulation during the COVID-19 pandemic in Germany

In stressful situations such as the COVID-19-pandemic, unpleasant emotions are expected to increase while pleasant emotions will likely decrease. Little is known about the role cognitive appraisals, information management, and upregulating pleasant emotions can play to support emotion regulation in a pandemic. In an online survey (N = 1682), we investigated predictors of changes in pleasant and unpleasant emotions in a German sample (aged 18–88 years) shortly after the first restrictions were imposed. Crisis self-efficacy and felt restriction were predictors of changes in unpleasant emotions and joy alike. The application of emotion up-regulation strategies was weakly associated with changes in joy. Among the different upregulation strategies, only “savouring the moment” predicted changes in joy. Our study informs future research perspectives assessing the role of upregulating pleasant emotions under challenging circumstances.

Constituents' Inferences of Local Governments' Goals and the Relationship Between Political Party and Belief in COVID-19 Misinformation: Cross-sectional Survey of Twitter Followers of State Public Health Departments

Background

Amid the COVID-19 pandemic, social media have influenced the circulation of health information. Public health agencies often use Twitter to disseminate and amplify the propagation of such information. Still, exposure to local government-endorsed COVID-19 public health information does not make one immune to believing misinformation. Moreover, not all health information on Twitter is accurate, and some users may believe misinformation and disinformation just as much as those who endorse more accurate information. This situation is complicated, given that elected officials may pursue a political agenda of re-election by downplaying the need for COVID-19 restrictions. The politically polarized nature of information and misinformation on social media in the United States has fueled a COVID-19 infodemic. Because pre-existing political beliefs can both facilitate and hinder persuasion, Twitter users' belief in COVID-19 misinformation is likely a function of their goal inferences about their local government agencies' motives for addressing the COVID-19 pandemic.

Objective

We shed light on the cognitive processes of goal understanding that underlie the relationship between partisanship and belief in health misinformation. We investigate how the valence of Twitter users' goal inferences of local governments' COVID-19 efforts predicts their belief in COVID-19 misinformation as a function of their political party affiliation.

Methods

We conducted a web-based cross-sectional survey of US Twitter users who followed their state's official Department of Public Health Twitter account (n=258) between August 10 and December 23, 2020. Inferences about local governments' goals, demographics, and belief in COVID-19 misinformation were measured. State political affiliation was controlled.

Results

Participants from all 50 states were included in the sample. An interaction emerged between political party affiliation and goal inference valence for belief in COVID-19 misinformation (∆R ²=0.04; F _8,249=4.78; P<.001); positive goal inference valence predicted increased belief in COVID-19 misinformation among Republicans (β=.47; t ₂₄₉=2.59; P=.01) but not among Democrats (β=.07; t ₂₄₉=0.84; P=.40).

Conclusions

Our results reveal that favorable inferences about local governments' COVID-19 efforts can accelerate belief in misinformation among Republican-identifying constituents. In other words, accurate COVID-19 transmission knowledge is a function of constituents' sentiment toward politicians rather than science, which has significant implications on public health efforts for minimizing the spread of the disease, as convincing misinformed constituents to practice safety measures might be a political issue just as much as it is a health one. Our work suggests that goal understanding processes matter for misinformation about COVID-19 among Republicans. Those responsible for future COVID-19 public health messaging aimed at increasing belief in valid information about COVID-19 should recognize the need to test persuasive appeals that address partisans' pre-existing political views in order to prevent individuals' goal inferences from interfering with public health messaging.

The moderating effects of entertainers on public engagement through government activities in social media during the COVID-19

Following the onset of COVID-19 pandemic, increasing the degree of public engagement is a crucial task for governments. This study investigated the moderating effects of entertainers on public engagement through government activities during COVID-19 pandemic. The government activities were publicized through the government's social media posts. The results showed a significant positive relationship between participation of entertainers and degree of public engagement through social media. Our findings indicated that inviting entertainers to participate could improve the effects of publicity and ease the emotional tension and anxiety among the public during a crisis. However, more attention should be paid to the choice of entertainers to maintain the legality and seriousness of government activities. These findings could help the government effectively communicate prevention policies and disseminate crisis information to the public, regardless of where they were physically located.

The Relationship between Government Information Supply and Public Information Demand in the Early Stage of COVID-19 in China-An Empirical Analysis

Accurate and effective government communication is essential for public health emergencies. To optimize the effectiveness of government crisis communication, this paper puts forward an analytical perspective of supply-demand matching based on the interaction between the government and the public. We investigate the stage characteristics and the topic evolutions of both government information supply and public information demand through combined statistical analysis, text mining, text coding and cluster analysis, using empirical data from the National Health Commission's WeChat in China. A quantitative measure reflecting the public demand for government information supply is proposed. Result indicates that the government has provided a large amount of high-intensity epidemic-related information, with six major topics being the medical team, government actions, scientific protection knowledge, epidemic situation, high-level deployment and global cooperation. The public's greatest information needs present different characteristics at different stages, with "scientific protection knowledge", "government actions" and "medical teams" being the most needed in the outbreak stage, the control stage and the stable stage, respectively. The subject of oversupply is "medical team", and the subject of short supply is "epidemic dynamics" and "science knowledge". This paper provides important theoretical and practical value for improving the effectiveness of government communication in public health crises.

Twitter Mediated Sociopolitical Communication During the COVID-19 Pandemic Crisis in India

While Twitter has grown popular among political leaders as a means of computer-mediated mass media communication alternative, the COVID-19 pandemic required new strategies for socio-political communication to handle such a crisis. Using the case of India, which was one of the worst-hit countries and is also the world's largest democracy, this research explicates how political leaders responded to the COVID-19 crisis on Twitter during the first wave as it was the first time such a crisis occurred. Theoretical frameworks of discursive leadership and situational crisis communication theory have been used to analyze interactions based on the usage patterns, the content of communication, the extent of usage in relation to the severity of the crisis, and the possible role of leaders' position along with the status of their political party. The sample consisted of tweets posted by six prominent political leaders in India across the four consecutive lockdown periods from 25th March to 31st May 2020. A total of 4,158 tweets were scrapped and after filtering for retweets, the final dataset consisted of 2,809 original tweets. Exploratory data analysis, sentiment analysis, and content analysis were conducted. It was found that the tweets had an overall positive sentiment, an important crisis management strategy. Four main themes emerged: crisis management information, strengthening followers' resilience and trust, reputation management, and leaders' proactiveness. By focusing on such discursive aspects of crisis management, the study comprehensively highlights how political interactions on twitter integrated with politics and governance to handle COVID-19 in India. The study has implications for the fields of digital media interaction, political communication, public relations, and crisis leadership.