In order to take advantage of the power of social media to promote vaccination, this study reveals the mechanisms of positive and negative impacts of social media news on vaccine hesitancy and vaccination behavior. Based on the stimulus-organism-response (S-O-R) framework, we developed a research model to understand the effects of vaccine safety news and risk news from social media (external stimuli) on individuals' psychological organism (i.e., safety perception and risk perception) and consequent behavioral response, vaccine hesitancy and vaccination behavior. The proposed model was tested by partial least square structural equation modeling (PLS-SEM) on a sample gathered in China from September 2021 to November 2021 and from February 2022 to April 2022 (valid responses = 1579). The results found that the relationship between vaccine risk news from social media and risk perception was higher than the relationship between vaccine safety news from social media and safety perception. Individuals are more sensitive to vaccine risk news than safety news on social media. Moreover, both safety perception and risk perception explained the critical psychological mechanisms behind vaccine hesitancy. Interestingly, ego network density mitigated the effect of safety news on safety perception and the effect of risk news on risk perception. The findings contribute to the S-O-R model, the research on social media effects, and the literature on vaccination attitudes and behaviors. This study also informs public health officials about leveraging the power of social media to motivate the public to accept the COVID-19 vaccines.

To comprehend the nature, implications, risks and consequences of the events of the COVID-19 crisis, individuals largely relied on various online information sources. The features of online information exchange (e.g., conducted on a massive scale, with an abundance of information and unverified sources) led to various behavioral and psychological responses that are not fully understood. This study therefore investigated the relationship between exposure to online information sources and how individuals sought, forwarded, and provided COVID-19 related information. Anchored in the stimulus-organism-response model, cognitive load theory, and the theory of fear appeal, this study examined the link between the online consumption of COVID-19-related information and psychological and behavioral responses. In the theory development process, we hypothesized the moderating role of levels of fear. The research model included six hypotheses and was empirically verified on self-reported data (N = 425), which was collected in early 2021. The results indicate that continuous exposure to online information sources led to perceived information overload, which further heightened the psychological state of cyberchondria. Moreover, the act of seeking and providing COVID-19 information was significantly predicted by perceived cyberchondria. The results also suggest that higher levels of fear led to increased levels of seeking and providing COVID-19-related information. The theoretical and practical implications of these findings are presented, along with promising areas for future research.

The COVID-19 pandemic has demonstrated the importance of large-scale campaigns to facilitate vaccination adherence. Social media presents unique opportunities to reach broader audiences and reduces the costs of conducting national or global campaigns aimed at achieving herd immunity. Nonetheless, few studies have reviewed the effectiveness of prior social media campaigns for vaccination adherence, and several prior studies have shown that social media campaigns do not increase uptake rates. Hence, our objective is to conduct a systematic review to examine the effectiveness of social media campaigns and to identify the reasons for the mixed results of prior studies. Our methodology began with a search of seven databases, which resulted in the identification of 92 interventions conducted over digital media. Out of these 92 studies, only 15 adopted social media campaigns for immunization. We analyzed these 15 studies, along with a coding scheme we developed based on reviews of both health interventions and social media campaigns. Multiple coders, who were knowledgeable about social media campaigns and healthcare, analyzed the 15 cases and obtained an acceptable level of inter-coder reliability (> .80). The results from our systematic review show that only a few social media campaigns have succeeded in enhancing vaccination adherence. In addition, few campaigns have utilized known critical success factors of social media to induce vaccination adherence. Based on these findings, we discuss a set of research questions that informatics scholars should consider when identifying opportunities for using social media to resolve one of the most resilient challenges in public health. Finally, we conclude by discussing how the insights drawn from our systematic reviews contribute to advancing theories, such as social influence and the health belief model, into the realm of social media-based health interventions.

The COVID-19 crisis has been a core threat to the lives of billions of individuals over the world. The COVID-19 crisis has influenced governments' aims to meet UN Sustainable Development Goals (SDGs); leading to exceptional conditions of fragility, poverty, job loss, and hunger all over the world. This study aims to investigate the current studies that concentrate on the COVID-19 crisis and its implications on SDGs using a bibliometric analysis approach. The study also deployed the Strengths, Weaknesses, Opportunities, and Threats (SWOT) approach to perform a systematic analysis of the SDGs, with an emphasis on the COVID-19 crisis impact on Malaysia. The results of the study indicated the unprecedented obstacles faced by countries to meet the UN's SDGs in terms of implementation, coordination, trade-off decisions, and regional issues. The study also stressed the impact of COVID-19 on the implementation of the SDGs focusing on the income, education, and health aspects. The outcomes highlighted the emerging opportunities of the crisis that include an improvement in the health sector, the adoption of online modes in education, the swift digital transformation, and the global focus on environmental issues. Our study demonstrated that, in the post-crisis time, the ratio of citizens in poverty could grow up more than the current national stated values. We stressed the need to design an international agreement to reconsider the implementation of SDGs, among which, are strategic schemes to identify vital and appropriate policies.

Misinformation exposure has attracted growing scholarly attention. While much research highlights misinformation exposure's negative impacts, this study argues that its positive effects should also be noted. By using a more precise measurement of misinformation exposure and a path model, this study outlines a path from misinformation exposure to anti-misinformation behaviors, partially mediated by misperceptions in the context of COVID-19. Findings indicate that exposure to popular but widely-denounced COVID-19 misinformation via social media had positive effects on verification intention. Frequent exposure to misinformation on social media is associated with lower misperceptions, suggesting a healthy dose of skepticism toward the platform and low internalization of misinformation. Special attention, however, needs to be paid to online news websites and personal contacts as misinformation sources. More tailored interventions and communication strategies to reduce misperceptions and increase media-literate behaviors are needed for younger, conservative, and ethnic minority individuals. Theoretical and practical implications are further discussed.

The extension of remote forms of employment, education and communication during the Covid-19 pandemic was expected to bridge the digital divide in 2020. However, more digitally developed countries have shown a reduction of Internet use. This article examines the changes in Internet use in 2020 as the first year of the Covid-19 pandemic focused on cross-country digital development. We use a random effects regression model to assess the relationship between Internet use as an indicator of digital divide and digital development on the macro, business, infrastructural, and individual levels in EU countries. Panel data from Eurostat for 2014-2020 are applied. We found that more digitally developed EU countries, including Estonia, the Netherlands, Denmark and Norway, show a higher relationship between Internet usage and digital performance than other EU countries. These countries saw a decrease in Internet use during 2020, which is contrary to the general trend of either increasing or unchanging Internet use in the case of social distancing restrictions and lockdowns. High digital dependence in more digitally developed countries, and in some other EU countries in the context of a pandemic as a crisis, has led to a reduction in Internet use due to the vulnerability of digitalized industries, enterprises, jobs and personal patterns that may identify the new challenge as inverted digital divide.

The COVID-19 pandemic has forced people to limit their physical interactions, which has led to explosive growth in online grocery shopping. However, there is no clear consensus in the retailing literature on whether consumers prefer to buy groceries online. The objective of this current study is to synthesize research about online grocery shopping published before and during the COVID-19 pandemic and to develop a conceptual framework about online grocery purchase intentions and their determinants, the mediation effects of consumers' attitudes, the moderating effects of COVID-19, and control variables. The -analysis presents data derived from 50 independent samples with a sample size of 20,538 respondents. Selected determinants were identified as triggers for online grocery purchase intentions, and perceived usefulness and consumer attitude were identified as important mediators between determinants and intentions. The findings clarify the mechanisms behind the increase in online grocery shopping during the pandemic by presenting a decrease in the importance of its strongest determinants (i.e., perceived usefulness and attitude). Based on these findings, we present contributions to theory, managerial implications, and future research directions.

The COVID-19 pandemic has disrupted the fitness landscape leading to phenomenal growth in virtual workouts. This study investigates factors influencing virtual workout team commitment and post-pandemic workout intentions. A conceptual framework is developed that is grounded in the social identity theory. Online data collection is employed to gather responses from 406 team virtual workout participants. Results reveal that virtual workout team participation positively influences team identification, satisfaction, and compliance with team norms. Additionally, virtual workout team identification, satisfaction, and compliance to team norms were found to be antecedents of commitment to the virtual workout team. Commitment to virtual workout teams is revealed to be positively associated with post-pandemic virtual team workout intention and post-pandemic traditional team workout intention. However, the relationship with post-pandemic traditional team workout intentions was found to be stronger. Valuable theoretical and practical insights emerge, providing a better understanding of virtual workout team commitment and how marketers and practitioners can ensure post-pandemic success by better understanding customer behaviour.

During the COVID-19 pandemic, television and social media informed and entertained people. This cross-sectional study among adolescents and young adults ( = 859, 71.94% female,  = 20.55,  = 4.59) examined the associations between pro- and anti-governmental (social) media and youth's violations of the lockdown measures following the prototype willingness model (PWM). Data were collected during Belgium's first and strictest lockdown. The results largely confirmed the applicability of the PWM in a public health context. Posting of and exposure to anti-governmental social media messages positively related to violations of the regulations via higher descriptive norm perceptions of peers violating the measures and positive attitudes towards violations. Pro-governmental media interactions (i.e., exposure to news media and pro-governmental social media messages) negatively related to violations via negative attitudes towards violations. No support emerged for the role of (televised) series, prototype favorability, or subjective norms in the PWM. Differences in posting versus exposure of social media messages were found. Posting generally related stronger to risk cognitions and behaviors compared to exposure. Gender and age moderated some of the examined relations in the PWM. Implications for media research and health campaigns are discussed.

The prevalence of severe infectious diseases has become a major global health concern. Currently, the COVID-19 outbreak has spread across the world and has created an unprecedented humanitarian crisis. The proliferation of novel viruses has put traditional health systems under immense pressure and posed several serious issues. Henceforth, early detection, identification, rapid testing, and advanced surveillance systems are required to address public health emergencies. However, Information and Communication Technology (ICT) tackles several issues raised by this pandemic and significantly improves the quality of services in the health care sector. This paper presents an ICT-assisted scientometric analysis of infectious diseases, namely, airborne, food & waterborne, fomite-borne, sexually transmitted illnesses, and vector-borne illnesses. It assesses the international research status of this field in terms of citation structure, prolific journals, and country contributions. It has used the CiteSpace tool to address the visualization needs and in-depth insights of scientific literature to pinpoint core hotspots, research frontiers, emerging research areas, and ICT trends. The research finding reveals that mobile apps, telemedicine, and artificial intelligence technologies have greater scope to reduce the threats of infectious diseases. COVID-19, influenza, HIV, and malaria viruses have been identified as research hotspots whereas COVID-19, contact tracing applications, security and privacy concerns about users' data are the recent challenges in this field that need to address. The United States has produced higher research output in all domains of infectious diseases. Furthermore, it explores the co-occurrence network analysis and intellectual landscape of each domain of infectious diseases. It provides potential research directions and insightful clues to researchers and the academic fraternity for further research.

Social media users share a variety of information and experiences and create Electronic Word of Mouth (eWOM) in the form of positive or negative opinions to communicate with others. In the context of the COVID-19 outbreak, eWOM has been an effective tool for knowledge sharing and decision making. This research aims to reveal what factors of eWOM can influence travelers' trust in their decision-making to travel during the COVID-19 outbreak. In addition, we aim to find the relationships between trust in eWOM and perceived risk, and perceived risk and the decision to travel. These relationships are investigated based on online customers' reviews in TripAdvisor's COVID-19 forums. We use a two-stage data analysis which includes cluster analysis and structural equation modeling. In the first stage, a questionnaire survey was designed and the data was collected from 1546 respondents by referring to the COVID-19 forums on TripAdvisor. Specifically, we use -means to segment the users' data into different groups. In the second stage, Structural Equation Modeling (SEM) was performed to inspect the relations between the variables in the hypothesized research model using a subsample of 679 respondents. The results of the first stage of the analysis showed that three segments could be discovered from the collected data for trust based on eWOM source and eWOM message attributes. These segments clearly showed that there are significant relationships between trust and perceived risk, and between perceived risk and the decision to travel. The results in all segments showed that users with a low level of trust have a high level of perceived risk and a low level of intention to travel during the COVID-19 outbreak. In addition, it was found that users with a high level of e-trust have a low level of perceived risk and a high level of intention to travel. These results were confirmed in all segments and these relationships were confirmed by SEM. The results of SEM revealed that visual and external information moderated the relationship between eWOM length and trust, and experience moderated the relationship between trust and perceived risk. For the moderating role of gender, it was found that the perceived risk has a higher impact on the decision to travel in the female sample.

Mobile-based health (mHealth) systems are proving to be a popular alternative to the traditional visits to healthcare providers. They can also be useful and effective in fighting the spread of infectious diseases, such as the COVID-19 pandemic. Even though young adults are the most prevalent mHealth user group, the relevant literature has overlooked their intention to invest in and use mHealth services. This study aims to investigate the predictors that influence young adults' intention to invest in mHealth (IINmH), particularly during the COVID-19 crisis, by designing a research methodology that incorporates both the health belief model (HBM) and the expectation-confirmation model (ECM). As an expansion of the integrated HBM-ECM model, this study proposes two additional predictors: mobile Internet speed and mobile Internet cost. A multi-method analytical approach, including partial least squares structural equation modelling (PLS-SEM), fuzzy-set qualitative comparative analysis (fsQCA), and machine learning (ML), was utilised together with a sample dataset of 558 respondents. The dataset-about young adults in Bangladesh with an experience of using mHealth-was obtained through a structured questionnaire to examine the complex causal relationships of the integrated model. The findings from PLS-SEM indicate that value-for-money, mobile Internet cost, health motivation, and confirmation of services all have a substantial impact on young adults' IINmH during the COVID-19 pandemic. At the same time, the fsQCA results indicate that a combination of predictors, instead of any individual predictor, had a significant impact on predicting IINmH. Among ML methods, the XGBoost classifier outperformed other classifiers in predicting the IINmH, which was then used to perform sensitivity analysis to determine the relevance of features. We expect this multi-method analytical approach to make a significant contribution to the mHealth domain as well as the broad information systems literature.

As the battle with COVID-19 continues, an Infodemic problem has been raised. Even though the distribution of false news in national disaster situations has been reported for a long time, little attention has been given to the quantitative research of the fake news problem from the audience's perspective. This study, therefore, aims to estimate how much tax taxpayers would gladly pay for a virtual public-run fact-checking system. Using a one-and-one-half bounded dichotomous choice contingent valuation method, a survey was conducted on 525 respondents in Korea, and the spike model was applied to distinguish zero willingness-to-pay (WTP). The results show that a household's WTP for the public fact-checking system is 10,652 KRW (9 USD), on average, in the form of income tax for five years. Given the amount is a regular payment in perpetuity, the total WTP is estimated at 23 billion KRW ($196 M) every year. The result also shows that an individual's WTP increases as his or her psychological damage caused by fake news is high, as well as his or her high reliance on news in a disaster situation.

The development and uptake of the COVID-19 (coronavirus disease 2019) vaccine is a top priority in stifling the COVID-19 pandemic. How the public perceives the COVID-19 vaccine is directly associated with vaccine compliance and vaccination coverage. This study takes a cultural sensitivity perspective and adopts two well-known social media platforms in the United States (Twitter) and China (Weibo) to conduct a public perception comparison around the COVID-19 vaccine. By implementing semantic network analysis, results demonstrate that the two countries' social media users overlapped in themes concerning domestic vaccination policies, priority groups, challenges from COVID-19 variants, and the global pandemic situation. However, Twitter users were prone to disclose individual vaccination experiences, express anti-vaccine attitudes. In comparison, Weibo users manifested evident deference to authorities and exhibited more positive feelings toward the COVID-19 vaccine. Those disparities were explained by the cultural characteristics' differences between the two countries. The findings provide insights into comprehending public health issues in cross-cultural contexts and illustrate the potential of utilizing social media to conduct health informatics studies and investigate public perceptions during public health crisis time.

The coronavirus disease 2019 (COVID-19) pandemic has impacted all aspects of people's lives, including how we work, play, learn, exercise, and socialize. Virtual reality (VR) technology has the potential to mitigate many of the challenges brought about by the pandemic, which has spurred increased adoption. However, relatively low adoption overall and limited software still restrict the power of VR to address COVID-19 difficulties effectively. This study examines how the perceived impacts of COVID-19 might lead to different VR uses and gratifications and device ownership / variability. Furthermore, we investigate the importance of social interactivity within VR for increasing adoption intentions. We surveyed 298 Amazon Mechanical Turk users during the Fall of 2020. Results indicate that the pandemic's perceived impacts influenced the likelihood of acquiring VR for education, tourism, and work. For VR ownership and variability, those who purchased VR during the pandemic were more likely to report buying it for work. Those with access to high-end VR hardware were more likely to report a broader range of uses, including socializing, health, and telemedicine. Validating the importance of various applications during the pandemic, we found that the desire for social interactivity mediates the impacts of COVID-19 on future adoption intentions. Theoretically, we propose several gratifications sought via the use of VR during the pandemic. Practically, we discuss recommendations for future VR research, marketing, and software design.

The COVID-19 pandemic has caused major global changes both in the areas of healthcare and economics. This pandemic has led, mainly due to conditions related to confinement, to major changes in consumer habits and behaviors. Although there have been several studies on the analysis of customers' satisfaction through survey-based and online customers' reviews, the impact of COVID-19 on customers' satisfaction has not been investigated so far. It is important to investigate dimensions of satisfaction from the online customers' reviews to reveal their preferences on the hotels' services during the COVID-19 outbreak. This study aims to reveal the travelers' satisfaction in Malaysian hotels during the COVID-19 outbreak through online customers' reviews. In addition, this study investigates whether service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. Accordingly, we develop a new method through machine learning approaches. The method is developed using text mining, clustering, and prediction learning techniques. We use Latent Dirichlet Allocation (LDA) for big data analysis to identify the voice-of-the-customer, Expectation-Maximization (EM) for clustering, and ANFIS for satisfaction level prediction. In addition, we use Higher-Order Singular Value Decomposition (HOSVD) for missing value imputation. The data was collected from TripAdvisor regarding the travelers' concerns in the form of online reviews on the COVID-19 outbreak and numerical ratings on hotel services from different perspectives. The results from the analysis of online customers' reviews revealed that service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. In addition, the results showed that although the customers are always seeking hotels with better performance, they are also concerned with the quality of related services in the COVID-19 outbreak.

Infodemic, the spread of false information during the COVID-19 pandemic, has been raised as one of the major concerns aggravating the confusion in the global society. In this regard, the role of media as an information channel in delivering the reliable information and motivating the active participation of citizens in complying with government's preventive actions becomes much more important. In this study, the role of online news and social media on people's preventive actions considering the role of trust in citizens and government from the perspective of social capital is investigated. For the empirical study, a structural equation modeling is employed by using survey material gathered from South Korea in the early days of the COVID-19 outbreak. South Korea was selected as its COVID-19 prevention strategy focused not only on the provision of medical support, but also on the enhancement of social trust through active engagement with people through media channels. Our results reveal that the perceived characteristics of online news and social media influence preventive actions through the trust in citizens or in government. In addition, while online news media enhances trust in both the citizens and the government, social media only influences trust in citizens. Based on our findings, the role of media in preventing the spread of COVID-19 is dicussed.

Social media has been increasingly utilized as an effective avenue for individuals to obtain needed social support and health-related information, especially during the on-going global COVID-19 pandemic. However, surprisingly few empirical studies have concentrated on the detrimental impact of social media adoption on young adults' psychosocial well-being and mental health. Drawing upon previous stressor-strain-outcome theoretical paradigm (SSO), the present research investigates how psychosocial well-being assessments, especially compulsive WeChat use and information overload could trigger social media fatigue and, furthermore, how social media fatigue would ultimately result in emotional stress and social anxiety. This article utilized the cross-sectional design whereby statistical data were collected from 566 young people to test the conceptual research model. This research results demonstrate that perceived information overload through WeChat could significantly trigger social media fatigue among young people. Moreover, perceived information overload could indirectly predict emotional stress and social anxiety through the mediation of social media fatigue. This present work has vital theoretical and practical implications for widespread adoption of newly emerging communication technologies to enhance mental health and well-being among younger generation during recent public health crises.

In this paper we refer to the Open Web to the set of services offered freely to Internet users, representing a pillar of modern societies. Despite its importance for society, it is unknown how the COVID-19 pandemic is affecting the Open Web. In this paper, we address this issue, focusing our analysis on Spain, one of the countries which have been most impacted by the pandemic. On the one hand, we study the impact of the pandemic in the financial backbone of the Open Web, the online advertising business. To this end, we leverage concepts from Supply-Demand economic theory to perform a careful analysis of the elasticity in the supply of ad-spaces to the financial shortage of the online advertising business and its subsequent reduction in ad spaces' price. On the other hand, we analyze the distribution of the Open Web composition across business categories and its evolution during the COVID-19 pandemic. These analyses are conducted between Jan 1st and Dec 31st, 2020, using a reference dataset comprising information from more than 18 billion ad spaces. Our results indicate that the Open Web has experienced a moderate shift in its composition across business categories. However, this change is not produced by the financial shortage of the online advertising business, because as our analysis shows, the Open Web's supply of ad spaces is inelastic (i.e., insensitive) to the sustained low-price of ad spaces during the pandemic. Instead, existing evidence suggests that the reported shift in the Open Web composition is likely due to the change in the users' online behavior (e.g., browsing and mobile apps utilization patterns).

Videoconferencing and teleworking have become indispensable for many public and private organizations since the appearance of COVID-19. However, the extent to which the pandemic may have a lasting effect on people's daily life and work remains to be seen. Poor visual and acoustic quality of online meetings could reactivate old communication patterns in the long term. New technologies such as 6G and 3D holography, offering enhanced video quality and online experience, could further drive virtualization in communication. This article investigates the CO mitigation potential resulting from the partial replacement of business travel by 6G-enabled 3D videoconferencing in Germany in 2030. The carbon footprint calculation combined with scenario analysis has shown significant results when direct and indirect energy effects are considered. In the different scenarios investigated, a virtual conference would cause between 0.2% and 0.9% of the emissions of a mean-distance conference trip taken by a German business traveler. Considering the mitigation potential of all German conference travel in 2030, emissions could be decreased by 2.1 MtCOeq (8.9%) and 20.5 MtCOeq (88.4%), respectively, compared to 2019 under conservative and optimistic assumptions. In terms of current national total emissions, increasing virtualization of conferences could contribute between 0.3% and 2.8% to the German mitigation efforts.

As the SARS-CoV-2 (COVID-19) pandemic has run rampant worldwide, the dissemination of misinformation has sown confusion on a global scale. Thus, understanding the propagation of fake news and implementing countermeasures has become exceedingly important to the well-being of society. To assist this cause, we produce a valuable dataset called FibVID (Fake news information-broadcasting dataset of COVID-19), which addresses COVID-19 and non-COVID news from three key angles. First, we provide truth and falsehood (T/F) indicators of news items, as labeled and validated by several fact-checking platforms (e.g., Snopes and Politifact). Second, we collect spurious-claim-related tweets and retweets from Twitter, one of the world's largest social networks. Third, we provide basic user information, including the terms and characteristics of "heavy fake news" user to present a better understanding of T/F claims in consideration of COVID-19. FibVID provides several significant contributions. It helps to uncover propagation patterns of news items and themes related to identifying their authenticity. It further helps catalog and identify the traits of users who engage in fake news diffusion. We also provide suggestions for future applications of FibVID with a few exploratory analyses to examine the effectiveness of the approaches used.