Message sharing and verification behaviour on social media during the COVID-19 pandemic: a study in the context of India and the USA

Users' unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one. Data from a sample of 646 users were analyzed using Structural Equation Modeling to assess the determinative effect of both the reasoned pathway (attitude toward unverified information-sharing, subjective norm, and perceived behavioral control) and the social-reaction pathway (prototype favorability and similarity). Findings highlight the substantial role of the social-reaction pathway in forecasting users' unverified information-sharing behavior, with prototype similarity and attitude being the dominant predictors. Meanwhile, components of the reasoned pathway, specifically perceived behavior control, and attitude, also exhibited significant contributions toward predicting the behavior. In summary, while a deliberate, reasoned process has some influence, the sharing of unverified information on social media by users is primarily an intuitive, spontaneous response to specific online circumstances. This study therefore offers valuable insights that could aid relevant stakeholders in effectively regulating the spread of misinformation. Against this backdrop, highlighting potential risks associated with sharing unverified information and the negative portrayal of users propagating misinformation may contribute to the development of a more critical perspective toward online information sharing by users themselves.

How does herd behaviour impact the purchase intention? Explore the moderating effect of risk aversion in the context of Vietnamese consumers

Managers have been applying the influence of herd behaviour to stimulate purchase intention but have not achieved precise results because they do not clearly understand the mechanism of this relationship. This article aims to determine the effect of herd behaviour on the relationship between information adoption and purchase intention and the moderating of risk aversion. With 17 variables for four concepts, data was collected online with 340 respondents and analysed with a partial least squares structural equation modelling. When considering herd behaviour in terms of subjective norms with corroborated information, this study upgrades the classic role of the theory of planned behaviour in purchase intention. The findings indicate a positive relationship between herd behaviour, information adoption and purchase intention. In particular, risk aversion is a positive moderator of the relationship between herd behaviour and purchase intention. This result is a significant addition to the theoretical body and shows that risk aversion can drive purchase intention through herd behaviour. In other words, this study upgrades the perception of information source authentication through herd behaviour to explain the purchase intentions of Vietnamese consumers. These results show that managers can create risky situations to promote herd behaviour. They can also apply information adoption stimuli to stimulate herd behaviour. At the same time, through the information adoption mechanism, consumers can be more alert to the effect of herd behaviour and have more opinions when making purchases.

Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China

The outbreak of information epidemic in crisis events, with the channel effect of social media, has brought severe challenges to global public health. Combining information, users and environment, understanding how emotional information spreads on social media plays a vital role in public opinion governance and affective comfort, preventing mass incidents and stabilizing the network order. Therefore, from the perspective of the information ecology and elaboration likelihood model (ELM), this study conducted a comparative analysis based on two large-scale datasets related to COVID-19 to explore the influence mechanism of sentiment on the forwarding volume, spreading depth and network influence of information dissemination. Based on machine learning and social network methods, topics, sentiments, and network variables are extracted from large-scale text data, and the dissemination characteristics and evolution rules of online public opinions in crisis events are further analyzed. The results show that negative sentiment positively affects the volume, depth, and influence compared with positive sentiment. In addition, information characteristics such as richness, authority, and topic influence moderate the relationship between sentiment and information dissemination. Therefore, the research can build a more comprehensive connection between the emotional reaction of network users and information dissemination and analyze the internal characteristics and evolution trend of online public opinion. Then it can help sentiment management and information release strategy when emergencies occur.

The moderating influence of perceived government information transparency on COVID-19 pandemic information adoption on social media systems

Introduction

Social media systems are instrumental in the dissemination of timely COVID-19 pandemic information to the general population and contribute to the fight against the pandemic and waves of disinformation during the COVID-19 pandemic. This study uses the information adoption model (IAM) as the theoretical framework to examine the moderating influence of perceived government information transparency on the adoption of COVID-19 pandemic information on social media systems from the Ghanaian perspective. Government information transparency regarding the pandemic is crucial since any lack of transparency can negatively affect the global response to the pandemic by destroying trust (in government and public health authorities/institutions), intensifying fears, and causing destructive behaviors.

Methods

It applies a convenient sampling technique to collect the responses from 516 participants by using self-administrated questionnaires. The data analysis was computed and analyzed with SPSS-22. The following statistical tests were conducted to test the hypotheses: descriptive statistics, scale reliability test, Pearson bivariate correlation, multiple linear regressions, hierarchical regression, and slope analysis.

Results

The results indicate that information quality, information credibility, and information usefulness are significant drivers of COVID-19 pandemic information adoption on social media systems. Furthermore, the perceived government information transparency positively moderates the influence of information quality, information credibility, and information usefulness on the adoption of COVID-19 pandemic information on social media systems.

Conclusion

The theoretical and managerial implications of these findings suggest the utilization of social media systems as an effective tool to support the continued fight against the current COVID-19 pandemic and its future role in national and global public health emergencies.

Fact-checking behaviors of undergraduate students

Obtaining fact-checking skills is becoming crucial as information disorder turns into a major issue for societies. The aim of this study is to evaluate the extent to which students benefited from the fact-checking module within the news literacy (NL) training and what kind of fact-checking behavior they exhibited. The research was conducted with two different groups of university students for two years using a quasi-experimental design method. Following the training, the students conducted their fact-checking process by making more queries, mainly using news titles, and mostly clicking on news platforms. Although many of the students did not show high performance after the training, it was seen that training created a certain awareness about the verification platforms/tools. The study highlighted the importance of information literacy skills in NL training provided at the university level and the characteristics that distinguish information behaviors during fact-checking from those in other information search processes.

Evaluating the elevation of authoritative health content online during the COVID-19 pandemic

Purpose

To respond to the COVID-19 “infodemic” and combat fraud and misinformation about the virus, social media platforms coordinated with government healthcare agencies around the world to elevate authoritative content about the novel coronavirus. These public health authorities included national and global public health organisations, such as the Centers for Disease Control and Prevention (CDC) and the World Health Organisation (WHO). In this article, the authors evaluate the effectiveness of this strategy by asking two key questions: (1) Did people engage with authoritative health content on social media? (2) Was this content trusted?

Design/methodology/approach

The authors explore these issues by drawing on data from a global online questionnaire on “Public Trust in Experts” (n = 429) conducted during the initial phase of the pandemic in May 2020, a crucial period when reliable information was urgently required to influence behaviour and minimise harm.

Findings

The authors found that while the majority of those surveyed noticed authoritative health content online, there remained significant issues in terms of Internet users trusting the information shared by government healthcare agencies and public health authorities online.

Originality/value

In what follows, the authors examine the role of trust in implementing this novel public health strategy and assess the capacity for such policies to reduce individual and social harm.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2021-0655

Social media exposure assessment: influence on attitudes toward generic vaccination during the COVID-19 pandemic

Purpose

Even though social media (SM) has been explored in-depth, its role remains unclear regarding short- and long-term preventive attitudes in global health emergencies. To fill this gap, the Stimulus-Organism-Response framework aims to clarify the social media exposure mission in acknowledging risk perception and triggering preventive attitudes and behaviors toward COVID-19 and general vaccination.

Design/methodology/approach

The authors conducted an explanatory-predictive study on 480 Romanian students, using partial least squares structural equation modeling, and performed model evaluation, multi-group, model selection, and importance-performance map analyses.

Findings

The study provides insights in understanding significant relationships and drivers explaining and predicting attitudes towards vaccines. The main relationships are between fear and risk perception; risk and preventive attitudes and behaviors; and vaccination degree and attitudes to vaccines. The most important factor is the vaccination degree and media exposure is the most performant.

Practical implications

Developing and applying regulations and communication strategies for quality mass information may positively increase attitudes toward vaccines by indirectly enforcing the main drivers.

Social implications

Organizations, authorities, and opinion leaders must have a coherent supportive presence in media.

Originality/value

This study filled the literature gap by building a generic theoretical and empirical proven framework that investigates the mediated effect towards vaccines of all media types by COVID-19 experience and vaccination degree.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2021-0621

A deep neural networks-based fusion model for COVID-19 rumor detection from online social media

Purpose

The COVID-19 has become a global pandemic, which has caused large number of deaths and huge economic losses. These losses are not only caused by the virus but also by the related rumors. Nowadays, online social media are quite popular, where billions of people express their opinions and propagate information. Rumors about COVID-19 posted on online social media usually spread rapidly; it is hard to analyze and detect rumors only by artificial processing. The purpose of this paper is to propose a novel model called the Topic-Comment-based Rumor Detection model (TopCom) to detect rumors as soon as possible.

Design/methodology/approach

The authors conducted COVID-19 rumor detection from Sina Weibo, one of the most widely used Chinese online social media. The authors constructed a dataset about COVID-19 from January 1 to June 30, 2020 with a web crawler, including both rumor and non-rumors. The rumor detection task is regarded as a binary classification problem. The proposed TopCom model exploits the topical memory networks to fuse latent topic information with original microblogs, which solves the sparsity problems brought by short-text microblogs. In addition, TopCom fuses comments with corresponding microblogs to further improve the performance.

Findings

Experimental results on a publicly available dataset and the proposed COVID dataset have shown superiority and efficiency compared with baselines. The authors further randomly selected microblogs posted from July 1–31, 2020 for the case study, which also shows the effectiveness and application prospects for detecting rumors about COVID-19 automatically.

Originality/value

The originality of TopCom lies in the fusion of latent topic information of original microblogs and corresponding comments with DNNs-based models for the COVID-19 rumor detection task, whose value is to help detect rumors automatically in a short time.

The application of emotions, sharing motivations, and psychological distance in examining the intention to share COVID-19-related fake news

Purpose

Coronavirus disease 2019-related fake news consistently appears on social media. This study uses appraisal theory to analyze the impact of such rumors on individuals' emotions, motivations, and intentions to share fake news. Furthermore, the concept of psychological distance and construal level theory are used in combination with appraisal theory to compare toilet paper shortages and celebrity scandal rumors.

Design/methodology/approach

Data collected from 299 Taiwanese respondents to 150 toilet paper shortage-related and 149 celebrity gossip-related questionnaires were processed using partial least squares regression and multigroup analysis.

Findings

In both cases, surprise is felt most intensely. However, unlike in the celebrity fake news scenario, worry plays a prominent role in driving the altruistic sharing motivation related to the toilet paper shortage rumor. Furthermore, while emotional attributes (basic or self-conscious, concrete, or abstract) serve as a guide for how emotions change with psychological distance, the degree to which an emotion is relevant to the fake news context is key to its manifestation.

Originality/value

This study examines the impact of individuals' emotions on their motivations and intention to share fake news, applying the appraisal theory and the psychological distance concept in a single study to fake news sharing intention. It evaluates the relationship between psychological distance and emotions, revealing that it is not absolute and need not necessarily shift according to psychological distance change; rather, the relationship is context-sensitive.

Sharing or Not: Psychological Motivations of Brand Rumors Spread and the Stop Solutions

Brand rumors can harm brands' image and bring significant impacts on customers' decision-making and sharing behavior. Finding practical strategies for preventing the spread of brand rumors continues to be a challenge. Building on the social contagion theory, the current research enriches the discussion on understanding why people spread rumors and how to deal with the spreading of rumors. Sharing brand rumors is motivated by a variety of complex psychological reasons, but prior research didn't adequately analyze the problem from a complexity perspective. Therefore, using a sample of 416 interviewers within eight types of brand rumors, this study employs fuzzy-set qualitative comparative analysis (fsQCA) to investigate the combination of rumor psychological communication motivations in brand activities and solutions to prevent the spread of brand rumors. The current study discoveries three and two first-level configurational solutions, respectively, that can promote positive and negative rumor spreading. To summarize, emotional stimulation is a key component in the spread of rumors; altruism and relationship management motivation can coexist at times; and untrusted rumors are disseminated through other motivation factors. Solutions to prevent rumors from spreading are also provided. Furthermore, the findings help to understand the psychology of configurational motivation and how it can help brands reduce the spread of brand rumors. Finally, these discoveries' theoretical contributions and practical implications are presented.

Perceived Information Overload and Unverified Information Sharing on WeChat Amid the COVID-19 Pandemic: A Moderated Mediation Model of Anxiety and Perceived Herd

Individuals' unverified information sharing on social media, namely, sharing information without verification, is a major cause of the widespread misinformation amid the COVID-19 pandemic. The association between perceived information overload and unverified information sharing has been well documented in the cognitive overload approach. However, little is known about the underlying mechanism of this process. This study aims to explore the mediating role of anxiety and the moderating role of perceived herd between perceived information overload and unverified information sharing on WeChat. Anxiety demonstrates people's emotional response to the pandemic, whereas perceived herd describes a willingness to share certain information if it has been shared by many. The results of an online survey in China (N = 525) showed that perceived information overload was positively associated with unverified information sharing. In addition, this relationship was partially mediated by anxiety. Moreover, perceived herd positively moderated the link between anxiety and unverified information sharing, such that the indirect effect of perceived information overload on unverified information sharing via anxiety was significant in conditions where the level of perceived herd was high, whereas the indirect effect was not significant in conditions where the level of perceived herd was low. The moderated mediation model extends the cognitive overload approach and indicates that unverified information sharing is not only an individual strategy to cope with information overload but also a herding behavior to manage anxiety. Practical implications for curbing people's tendencies toward unverified information sharing on social media are discussed.