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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 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

Drawing upon the third-person effect (TPE) theory, this study focuses on two types of misinformation countering intentions (i.e. simple correction and correction with justification). Accordingly, it aims to (1) assess the tenability of the third-person perception (TPP) in the face of misinformation on social media, (2) explore the antecedents of TPP and its relationship with individual-level misinformation countering intentions and (3) examine whether the mediating process is contingent on different social media usage conditions.

An online survey was conducted with 1,000 representative respondents recruited in Mainland China in January 2022 using quota sampling. Paired t-test, multiple linear regression and moderated mediation analysis were employed to examine the proposed hypotheses.

Results bolster the fundamental proposition of TPP that individuals perceive others as more susceptible to social media misinformation than they are. The self-other perceptual bias served as a mediator between the perceived consequence of misinformation and misinformation countering (i.e. simple correction and correction with justification) intentions. Furthermore, intensive social media users were likely to be motivated to counter social media misinformation derived from the indirect mechanism.

The findings provide further evidence for the role of TPE in explaining misinformation countering intention as prosocial and altruistic behavior rather than self-serving behavior. Practically, promising ways to combat rampant misinformation on social media include promoting the prosocial aspects and beneficial outcomes of misinformation countering efforts to others, as well as reconfiguring the strategies by impelling intensive social media users to participate in enacting countering actions

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2022-0507.

The ballooning health misinformation on social media raises grave concerns. Drawing upon the S-O-R (Stimulus-Organism-Response) model and the information processing literature, this study aims to explore (1) how social media health information seeking (S) affects health misinformation sharing intention (R) through the channel of health misperceptions (O) and (2) whether the mediation process would be contingent upon different information processing predispositions.

Data were collected from a survey comprising 388 respondents from the Chinese middle-aged or above group, one of China's most susceptible populations to health misinformation. Standard multiple linear regression models and the PROCESS Macro were adopted to examine the direct effect and the moderated mediation model.

Results bolstered the S-O-R-based mechanism, in which health misperceptions mediated social media health information seeking's effect on health misinformation sharing intention. As an indicator of analytical information processing, need for cognition (NFC) failed to moderate the mediation process. Contrarily, faith in intuition (FI), an indicator reflecting intuitive information processing, served as a significant moderator. The positive association between social media health information seeking and misperceptions was stronger among respondents with low FI.

This study sheds light on health misinformation sharing research by bridging health information seeking, information internalization and information sharing. Moreover, the authors extended the S-O-R model by integrating information processing predispositions, which differs this study from previous literature and advances the extant understanding of how information processing styles work in the face of online health misinformation. The particular age group and the Chinese context further inform context-specific implications regarding online health misinformation regulation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0157.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

Misperceptions hinder our ability to effectively respond to health crises such as the COVID-19. We aimed to examine the dynamic influences between information exposure, information trust and misperceptions during the early phase of the COVID-19 pandemic. Specifically, we focused on the relative influence of exposure to COVID-19-related information via social media versus interpersonal offline communication.

The current study conducted a two-wave national survey of US adults in May and June of 2020 with a two-week time interval. A professional polling firm recruited participants, and 911 and 679 respondents participated in the first and the second wave survey, respectively. To test proposed hypotheses, researchers conducted path analyses using AMOS 27.0.

Findings show that individuals exposed to COVID-19-related information via social media are likely to hold increased misperceptions. In contrast, exposure to COVID-19-related information offline did not elicit any effects on misperceptions. The exposure to information on social media was positively associated with trust in that information, which, in turn, contributed to an increase in misperceptions. Furthermore, when examining the effects of misperception, it was found that misperceptions increased the likelihood of individuals being exposed to and having trust in COVID-19-related information on social media. The findings provide valuable insights into the role of social media as a platform where a detrimental cycle thrives, shaping the formation of misperceptions and cultivating a heightened dependence among individuals with elevated misperceptions.

The current study significantly extends the findings of prior research by examining the differential effects of social media and interpersonal communication offline on misperception and by revealing the intricate dynamics between information exposure and misperception by focusing on the role of trust. The findings emphasize the detrimental role of social media in generating a vicious information cycle. That said, seemingly superficial discussions about health crises within a social media environment rich in misinformation can contribute to fueling a self-reinforcing loop, making it challenging to effectively counteract misperceptions.

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.

This conceptual paper aims to explore the current state of sustainability communication research, focusing on the challenges of communicating inconvenient truths in an era of scientific mistrust. Therefore, this study aims to (1) examine the existing research landscape in sustainability communication, (2) identify unresolved problems and challenges, and (3) propose strategies for counteract misinformation through targeted communication.

For this, the authors conducted a critical literature review and analyzed the resulting sample (n = 473 journal articles) by means of qualitative content analysis to (1) evaluate existing communication approaches dealing with the communication of sustainability's inconvenient truth, (2) identify stakeholder groups involved in sustainability communication, (3) discuss limitations of current communication approaches and (4) present recommendations on (more) effective communication strategies to address the unresolved issues in sustainability communication.

The analysis reveals that when it comes to sustainability communication and its unresolved problems, literature refers to four key stakeholder groups: (1) science deniers; (2) adaptation skeptics; (3) whitewashers and (4) world saviors. Furthermore, the analysis provides valuable insights into the complex dynamics involved in communicating sustainability, emphasizes the need for tailored approaches to engage and address the concerns of each stakeholder group, and exposes limitations in current communication methods and approaches. Accordingly, the analysis highlights the necessity of developing new theories, models and methods specific to sustainability communication to tackle its unique challenges effectively.

Like our society, communication sciences need a fundamental transformation to meet sustainability communication's new challenges induced by the necessary shift toward sustainable development.

This paper provides a comprehensive overview of the current state of sustainability communication in research, specifically addressing the challenges of effectively communicating unpleasant news in the context of scientific mistrust. It fills a gap in existing literature by examining the progress made in addressing these issues and identifying the emerging challenges that need to be addressed.

Although there is a growing body of work on immigrants' information behavior, little is known about the pre-arrival information experiences of immigrants who consult formal information sources such as immigration agents. Drawn from a larger study on the information behavior of immigrants, this paper mainly reports the semi-structured interview findings on the pre-arrival information experiences of Bangladeshi immigrants who used formal information sources with discussion on how that affected their post-arrival settlement into Canada.

The study used a mixed method approach with semi-structured interviews (n = 60) and surveys (n = 205) with participants who arrived in Canada between the years of 1971 and 2017. Data were collected from May 2017 to February 2018.

Although the overall scope of the original study is much larger, this paper features findings on the pre-arrival information experiences derived mainly from an analysis of interview data. This study provides insights into the pre-arrival information experiences of Bangladeshi immigrants consulting formal information sources such as immigration firms, individual immigration consultants and more formal government agencies. The author introduces a new concept of “information crafting” by exploring the negative consequences of selective information sharing by immigration consultants/agents in newcomers' settlements in Canada, primarily positive information about life in Canada, sometimes with exaggeration and falsification. The interview participants shared story after the story of the settlement challenges they faced after arriving in Canada and how the expectations they built through the information received from immigration consultants and government agencies did not match after arrival. This study emphasizes the importance of providing comprehensive information about life in Canada to potential newcomers so that they can make informed decisions even before they apply.

The findings of this study have theoretical and practical implications for policy and research. This study provides insights into the complicated culturally situated pre-arrival information experiences of Bangladeshi immigrants. Moreover, the study findings encourage researchers in various disciplines, including psychology, migration studies and geography, to delve more deeply into newcomers' information experiences using an informational lens to examine the information newcomers receive from diverse sources and their effects on their post-arrival settlement in a new country. The study challenges the general assumptions that formal information sources are always reputable, useful, and comprehensive, and it provides some future directions for research that seeks to understand the culturally situated information behavior of diverse immigrant groups.

Social media have been playing a critical role in seeking and sharing health related information and consequently shaping individuals’ health behaviors. This study investigates how information seeking about Covid-19 vaccine on social media is related to vaccine receiving intentions. The study furthers explores the association of trust in social media and uncertainty about Covid-19 with information seeking and the moderating role of prior social media experience on this association.

We developed a questionnaire and collected data from 525 educated social media users through “Google Forms.” Further, we applied ordinary least squares (OLS) regress to test the study hypothesis.

We noted that trust in social media and uncertainty about Covid-19 vaccine positively influenced information seeking which further positively affected vaccine receiving intentions. However, the moderating effect of prior social media experience was not only noted as weak but also found negatively affecting the associations of trust in social media and uncertainty about Covid-19 vaccine with information seeking.

The findings provide insights into understanding of public perceptions regarding Covid-19 vaccine in the cultural contexts of a developing country. Further, it informs about the public patterns of seeking information related to health issues on social media, an understanding which may likely benefit policymakers, health care providers and researchers to understand the antecedents and behavioral outcomes of seeking information through social media during health crisis. The study also elucidates the leveraging power of social media to motivate the public to accept the Covid-19 vaccines.

The study uniquely combines the antecedents and behavioral outcomes of information seeking through social media in the particular context of Covid-19. It further extends the literature by introducing the conditional role of prior social media experience.