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This study aimed to uncover the characteristics of both misinformation and refutations as well as the associations between different aspects of misinformation and corresponding ways of rebutting it.

Leveraging Hovland's persuasion theory as a research lens and taking data from two Chinese refutation platforms, we characterized the topics of COVID-19-related misinformation and refutations, misinformation communicator, persuasion strategies of misinformation, refutation communicators and refutation strategies based on content analysis. Then, logistic regressions were undertaken to examine how the characteristics of misinformation and refutation strategies interacted.

The investigation into the association between misinformation and refutations found that distinct refutation strategies are favored when debunking particular types of misinformation and by various kinds of refutation communicators. In addition, several patterns of persuasion strategies were identified.

This study had theoretical and practical implications. It emphasized how misinformation and refutations interacted from the perspective of Hovland's persuasion theory, extending the scope of the existing literature and expanding the classical theory to a new research scenario. In addition, several patterns of persuasion strategies used in misinformation and refutation were detected, which may contribute to the refutation practice and help people become immune to misinformation.

This research is among the first to analyze the relationships between misinformation and refutation strategies. Second, we investigated the persuasion strategies of misinformation and refutations, contributing to the concerning literature. Third, elaborating on Hovland’s persuasion theory, this study proposed a comprehensive framework for analyzing the misinformation and refutations in China during the COVID-19 pandemic.

The mounting health misinformation on social media triggers heated discussions about how to address it. Anchored by the influence of presumed influence (IPI) model, this study investigates the underlying process of intentions to combat health misinformation. Specifically, we analyzed how presumed exposure of others and presumed influence on others affect intentions to practice pre-emptive and reactive misinformation countering strategies.

Covariance-based structural equation modeling based on survey data from 690 Chinese participants was performed using the “lavaan” package in R to examine the proposed mechanism.

Personal attention to health information on social media is positively associated with presumed others’ attention to the same information, which, in turn, is related to an increased perception of health misinformation’s influence on others. The presumed influence is further positively tied to two pre-emptive countermeasures (i.e. support for media literacy interventions and institutional verification intention) and one reactive countermeasure (i.e. misinformation correction intention). However, the relationship between presumed influence and support for governmental restrictions, as another reactive countering method, is not significant.

This study supplements the misinformation countering literature by examining IPI’s tenability in explaining why individuals engage in combating misinformation. Both pre-emptive and reactive strategies were considered, enabling a panoramic view of the motivators of misinformation countering compared to previous studies. Our findings also inform the necessity of adopting a context-specific perspective and crafting other-oriented messages to motivate users’ initiative in implementing corrective actions.

This study examines the role of crowd wisdom in misinformation correction. Going beyond fact-checking, we investigate the mechanisms underlying laypeople’s participation in misinformation correction. Drawing upon the Norm Activation Model (NAM), this study conceptualizes misinformation correction as a prosocial behavior and examines the impact of various media and social psychological factors on laypeople’s motivations to engage misinformation correction behavior.

Through a national survey of 1,022 respondents, we explore the norm activation process triggered by the perceived prevalence of online misinformation, which directly and indirectly impacts online misinformation correction intentions via awareness, norms, and efficacy. This mechanism was tested using structural equation modeling.

This study found that perceived prevalence of misinformation, self-efficacy, and outcome efficacy play multilayered roles in shaping misinformation correction intentions. The effects were mediated by the activation of personal norms, which showed the strongest direct relationship with correction intentions. However, these factors also demonstrated direct associations with correction intentions, indicating multiple paths in misinformation correction.

Differing from mainstream fact-checking approaches, this study provides a more comprehensive examination of the mechanisms underlying laypeople’s willingness to engage in social media misinformation correction behaviors. In addition, this study also extends NAM by incorporating media environment (perceived prevalence of online misinformation) into the model, identifying more paths affecting misinformation correction behaviors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0437

The proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.

A total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.

Results indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.

This study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505

This study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.

We proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.

The effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.

When exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.

Perceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.

Although there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.

The mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167

This chapter examines the impact of information digitization on the rise of misinformation, and the broader implications that this has for democracy. It is based on the Researching Students Information Choices (RSIC) project, which looks at how students evaluate scientific information on the internet.¹ Part of this study looked at container collapse.

In previous decades, information was contained in a physical book, newspaper, journal, magazine, or the like. These containers offered important contextual information about the origin and validity of the information. With information digitized, this context is lost. This can facilitate misinformation, as people might make incorrect judgments about information credibility because of the lack of context.

It is vital that citizens have the information literacy skills to initially evaluate information correctly. One possibility for misinformation being pervasive is that, once encoded, it becomes resistant to correction. This underscores the importance of teaching students to evaluate the credibility of information prior to the point of encoding.

To combat misinformation, librarians can teach students to evaluate containers and the indicators of credibility that they provide. Information containers can be evaluated prior to consuming information within a resource, while fact-checking only can happen after. Because of this, container evaluation can help prevent misinformation from being encoded. Our research demonstrates that this requires thoughtful engagement with the information resources and critical evaluation of the sources that produced them, and that students cannot accurately identify containers when they rely on heuristics like the URL and Google snippet.

Misinformation can influence decision-making by fueling individual's belief, prejudices, and stereotypes. In the context of international trade, misinformation refers to the spread of false or misleading information and facts mostly with the malicious intent of maligning reputation of products, services, trade policies of a country and thus negatively influencing liberal trade policies toward that country. Stereotypes and prejudices fueled by misinformation coupled with economic nationalism and populism cast a dark shadow over the liberal international order. Exaggerated claims about unfair trade practices laced with stereotypes, prejudices, and misinformation can fuel tensions and may eventually lead to trade dispute and retaliatory action such as the imposition of tariffs or breakdown of trade blocs. Fake News, as a term, came into prominence recently during the 2016 US elections. The spread of fake news during the election generated remarkable interest among researchers. While most research focused on the effect of misinformation, a few studies have shown the influence of misinformation in changing trade preferences. The intricate connection among trading partners can propagate misinformation. Misinformation can lead policymakers to undertake protectionist policies. However, policies driven by misinformation, taken by major economies, can have strong rippling effects on other trading partners because of their strong network connectedness. Therefore, it motivates us to understand and evaluate international trade in terms of network statistics. This chapter provides an in-depth analysis of the network effects of some major and emerging economic powers involved in bilateral or multilateral trade agreements.

Health misinformation on social media threatens public health. A critical question that sheds light on the propagation of health misinformation across social media platforms revolves around identifying the specific types of social media users susceptible to this issue. This study provides an initial insight into this matter by examining the underlying psychological mechanism that renders users susceptible to health misinformation.

In this study, we developed an integrated model of susceptibility to health misinformation, drawing on the motivation-opportunity-ability theory and the elaboration likelihood model. We collected the data from a sample of 342 social media users in China. Furthermore, the fuzzy-set qualitative comparative analysis was adopted to examine the proposed model and uncover the causal recipes associated with susceptibility to health misinformation.

The results indicated that there are three configural types of users that are susceptible to health misinformation: the health-consciousness core-driven type, the popularity-driven core type and the dual-driven type characterized by both high health consciousness and information popularity. Among these, high health-consciousness and the reliance on information popularity-based pathways emerge as pivotal factors influencing susceptibility to health misinformation.

This study contributes to the social media literature by identifying various psychological traits that lead to social media users’ susceptibility to health misinformation. Additionally, the study provides comprehensive guidance on how to mitigate the spread of health misinformation.

This study investigates the communication behavior of public health organizations on Twitter during the COVID-19 vaccination campaign in Brazil. It contributes to the understanding of the organizational framing of health communication by showcasing several instances of framing devices that borrow from (Brazilian) internet culture. The investigation of this case extends the knowledge by providing a rich description of the organizational framing of health communication to combat misinformation in a politically charged environment.

The authors collected a Twitter dataset of 77,527 tweets and analyzed a purposeful subsample of 536 tweets that contained information provided by Brazilian public health organizations about COVID-19 vaccination campaigns. The data analysis was carried out quantitatively and qualitatively by combining social media analytics techniques and frame analysis.

The analysis showed that Brazilian health organizations used several framing devices that have been identified by previous literature such as hashtags, links, emojis or images. However, the analysis also unearthed hitherto unknown visual framing devices for misinformation prevention and debunking that borrow from internet culture such as “infographics,” “pop culture references” and “internet-native symbolism.”

First, the identification of framing devices relating to internet culture add to our understanding of the so far little addressed framing of misinformation combat messages. The case of Brazilian health organizations provides a novel perspective to knowledge by offering a notion of internet-native symbols (e.g. humor, memes) and popular culture references for misinformation combat, including misinformation prevention. Second, this study introduces a frontier of political contextualization to misinformation research that does not relate to the partisanship of the spreaders but that relates to the political dilemmas of public organizations with a commitment to provide accurate information to citizens.

The findings inform decision-makers and public health organizations about framing devices that are tailored to internet-native audiences and can guide strategies to carry out information campaigns in misinformation-laden social media environments.

The findings of this case study expose the often-overlooked cultural peculiarities of framing information campaigns on social media. The report of this study from a country in the Global South helps to contrast several assumptions and strategies that are prevalent in (health) discourses in Western societies and scholarship.

This study uncovers unconventional and barely addressed framing devices of health organizations operating in Brazil, which provides a novel perspective to the body of research on misinformation. It contributes to existing knowledge about frame analysis and broadens the understanding of frame devices borrowing from internet culture. It is a call for a frontier in misinformation research that deals with internet culture as part of organizational strategies for successful misinformation combat.