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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

Purpose: The main purpose of the study is to understand the factors that facilitate correction behavior among individuals. In this study the authors examine the impact of self-perceived media literacy (SPML) and reflection on participants’ correction behavior.

Methods: Data for the study were collected from Amazon's MTurk using an online survey. Data were collected after a certificate of exemption was received by the Institutional Review Board in a research university in the United States (US) Qualtrics software was used to collect data. The total number of participants was 797.

Findings: The findings show that although both SPML and reflection are positively associated with rumor refutation, higher SPML alone is not enough. Reflective judgment is critical for individuals to take part in this behavior online, such that individuals with higher reflective judgment indicated that they refute rumors online, irrespective of their SPML score.

Originality: The authors tested the relationship of multiple variables with participants correction behavior. Although research shows the importance of social correction, there is not much knowledge about what facilitates actual misinformation correction.

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.

This research aims to explores consumers' motives and attitudes toward misinformation (fake reviews), its characteristics and its impact on individuals, brands and firms.

A thematic analysis was undertaken to meet the research objectives by analyzing qualitative data from in-depth interviews with a diverse sample (N = 48).

The findings indicate that altruism, impression management, matching ideologies, message appeal and perceived source power are the critical motivations for individuals to share misinformation. Misinformation leads to conflicts and avoidance among individuals and harms brand's reputation.

This study utilizes thematic analysis to extend and contribute to the literature on misinformation. The current research provides an overarching framework to decode the misinformation phenomenon for researchers and practitioners.

This study offers valuable insights to marketers to develop strategies to tackle the menace of false information to safeguard brand reputation.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of 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.

Misinformation is notoriously difficult to combat. Although social media firms have focused on combating the publication of misinformation, misinformation accusations, an important by-product of the spread of misinformation, have been neglected. The authors offer insights into factors contributing to the spread of misinformation accusations on social media platforms.

The authors use a corpus of 234,556 tweets about the 2020 US presidential election (Study 1) and 99,032 tweets about the 2022 US midterm elections (Study 2) to show how the sharing of misinformation accusations is explained by locomotion orientation.

The study findings indicate that the sharing of misinformation accusations is explained by writers' lower locomotion orientation, which is amplified among liberal tweet writers.

Practitioners and policymakers can use the study findings to track and reduce the spread of misinformation accusations by developing algorithms to analyze the language of posts. A limitation of this research is that it focuses on political misinformation accusations. Future research in different contexts, such as vaccines, would be pertinent.

The authors show how social media firms can identify messages containing misinformation accusations with the potential to become viral by considering the tweet writer's locomotion language and geographical data.

Early identification of messages containing misinformation accusations can help to improve the quality of the political conversation and electoral decision-making.

Strategies used by social media platforms to identify misinformation lack scale and perform poorly, making it important for social media platforms to manage misinformation accusations in an effort to retain trust. The authors identify linguistic and geographical factors that drive misinformation accusation retweets.

Drawing upon social cognitive theory, this study aims to investigate the potential predictors and consequences of social media health-misinformation seeking behavior during the coronavirus (COVID-19) pandemic.

Using a sample of 230 international students studying at Wuhan University and Beijing Language and Cultural University, China, this study employs structural equation modeling to analyze the collected data.

The results indicate that personal factors such as lack of health information literacy, environmental factors, information overload and social media peer influence have a significant effect on behavior, namely social media health-misinformation seeking behavior, which further influences outcomes, namely social media users' anxiety during the COVID-19 pandemic. In addition, both lack of health information literacy and social media peer influence have significant and direct effects on social media users' anxiety. However, the direct effect of information overload on social media users' anxiety is insignificant.

First, this study contributes to the literature on the individuals' social media health-misinformation seeking behavior, its precursors and its consequences, specifically on their mental healthcare during a pandemic situation. Second, this research is one of the pioneer studies that extend social cognitive theory to the context of social media health-misinformation seeking behavior and users' anxiety relationship.

This study aims to propose a model that delineated the diffusion process of product-harm misinformation on social media. Drawing on theoretical insights from cue diagnosticity and corporate associations, the proposed model mapped out how consumers' information skepticism and perceived content credibility influence their perceived diagnosticity of the product-harm misinformation and corporate ability (CA) associations with the company being impacted, which in turn influenced their trust toward the company and negative word-of-mouth (NWOM) intention.

A survey was conducted with 504 US consumers to empirically test the proposed model. Following the survey, in-depth interviews were conducted with 11 communication professionals regarding the applicability of the model.

When exposed to product-harm misinformation on social media, consumers' perceived diagnosticity of misinformation was negatively impacted by their information skepticism and positively impacted by perceived content credibility of misinformation. Perceived diagnosticity of product-harm misinformation negatively impacted consumers' CA associations, which then led to decreased trust and increased NWOM intention. Findings from the interviews further supported the diffusion process and provided insights on strategies to combat product-harm misinformation. Strategies shared by the interviewees included preparedness and social listening, proactive outreach and building strong CA associations as preventative measures.

This study incorporates the theoretical frameworks of cue diagnosticity and corporate associations into the scholarship of misinformation and specifically addresses the unique diffusion process of product-harm misinformation on social media. This study provides insights and tangible recommendations for communication professionals to combat product-harm misinformation.