Purpose The effective use of digital technology by farmers is contingent upon their digital behaviour, specifically, whether they predominantly engage in information seeking or entertainment consumption, which is affected by digital literacy. This paper aims to examine farmers' digital behaviour and digital literacy, as well as their relationship. Design/methodology/approach Data from the 2023 Digital Literacy Survey, initiated by the Ministry of Communications and Digital, Republic of Indonesia, were used in this study. Data analysis began with: (1) data preprocessing to ensure the data were clean and consistent (2) hierarchical cluster analysis of digital behaviour and digital literacy (3) heatmap analysis which is a matrix commonly used to identify patterns, relationships, and intensities in one dimension (4) Prediction of digital behaviour based on digital literacy and demographics (age, gender, digital spending, and education) using multinomial regression. Findings The results revealed that most Indonesian farmers exhibit a low-to-moderate intention to use digital technology, and they use it in a balanced manner for both information seeking and entertainment consumption. Regarding digital literacy, most Indonesian farmers exhibit a level ranging from low to moderate. There is a correlation between farmers' digital literacy and their digital behaviour. Higher levels of digital literacy prevent farmers from prioritising entertainment consumption. Furthermore, age, education, and gender affect farmers' digital behaviour. Research limitations/implications To evaluate the factors that influence the digital behaviour of farmers, this paper solely uses three demographic variables: age, education, and gender, due to the limited availability of data. The relatively low pseudo-R2 value (ranging from 0.0235 to 0.0968) implies that digital usage patterns are still influenced by other factors that have not been incorporated into this model. Therefore, to enhance the findings of this paper, it is recommended that future studies incorporate additional demographic and socio-economic factors. Moreover, future studies are also encouraged to examine the effect of farmers' digital behaviour on their farming situations, such as crop yield and profit, as well as access to production inputs, markets, funding, and technology. Practical implications This study provides practical insights for agricultural industry actors: the government, NGOs, and farmers. Collaboration is crucial to designing a digital literacy program that is tailored to and in line with the digital behaviour profile of farmers. Digital behavior allows farmers to be clustered into beginner, intermediate , and advanced farmers. This identification allows the development of interventions tailored to the specific needs of each group. The findings of this research can also serve as a guide for developing digital farming tools that suit farmers' needs, tailor technology to farmers' digital literacy levels, encourage wider adoption of technology, and support sustainable rural digital transformation. Social implications This study illustrates how digital literacy gaps in Indonesian farming communities can affect their ability to access information and participate in the digital economy. The findings reveal that low digital competency can deepen social exclusion and widen the gap between rural and urban areas. By identifying these distinct clusters of digital literacy and behaviour, this study supports evidence-based interventions to promote digital inclusion in rural settings, improve livelihoods, and promote equitable development in rural areas. Originality/value This study highlights the dual role of digital technology as a “double-edged sword” for farmers. The vast potential of technology allows for increased agricultural productivity, expanded access to information, easier market affordability, and other services. On the other hand, existing technology can trap farmers with low literacy into dwelling only on excessive entertainment content, so that technological advances have minimal economic impact and limited capacity development for farmers. Peer review The peer review history for this article is available at: Link to the website.
Purpose In the social media era, cyberspace can foster undesirable norms that erode moral boundaries and fuel cyber aggression, especially among young people. Integrating the Theory of Normative Social Behavior and the Theory of Planned Behavior, this study systematically explores how external norm (online social norm [OSN]) and internal norm (group consistency [GC]) influence Chinese youth’s online aggressive behavior (OAB) through the mechanism of moral disengagement (MD). Design/methodology/approach A survey was conducted among 1,092 Chinese young people via a professional online platform. Structural equation modeling was conducted using Analysis of Moment Structures (AMOS), version 24.0, whereas PROCESS Macro version 3.4 was employed to examine the hypothesized moderation effects within the proposed framework. Findings Both OSN and GC are positively correlated with OAB; GC significantly strengthens the relationship between OSN and OAB; MD positively mediates the relationship between OSN and OAB. Critically, within the Chinese collectivist context, external norms are more likely to activate MD among youth than internal norms. Originality/value This research investigated the normative formation mechanism of OAB, clarifying that within the Chinese collectivist culture, the external norm is more likely to activate the MD mechanism. This provides empirical evidence for normative theory within a non-Western cultural context. The study reveals a deep-seated cultural logic of moral norm operation. These findings offer a theoretical basis for understanding online deviance and provide new avenues for cross-cultural cyber governance and the cultivation of future digital citizenship. Peer review The peer review history for this article is available at: Link to the website
Purpose This study investigates how public engagement in political discourse on Facebook evolves during periods of continuous political instability. While prior research has examined engagement drivers during routine and election periods, this study focuses on how political communication and public responsiveness change across repeated election cycles under sustained crisis conditions. Design/methodology/approach Using computational methods, we examined more than 8,000 posts published by leading Israeli politicians and millions of public responses across four election cycles (2019–2021). The analysis tracks changes in sentiment, content features and communication patterns and examines their associations with public engagement as the political instability persisted. Findings Results reveal several notable patterns. Although negative sentiment dominated across all four campaigns, negativity consistently declined over time. Contrary to expectations, longer posts were associated with higher engagement. Overall, public engagement increased during the first three election cycles and then stabilized slightly in the fourth, suggesting competing dynamics of heightened political attention and gradual fatigue during prolonged instability. Originality/value This study provides a longitudinal examination of political discourse and engagement during an extended period of political instability. By jointly examining sentiment, content characteristics and engagement indicators, it contributes to understanding how online political communication evolves under prolonged crisis conditions and how competing dynamics of emotional amplification, heightened public attention and electoral fatigue may shape engagement over time. Peer review The peer review history for this article is available at: Link to the website.
Purpose This study examines how the political attributes of top prime minister candidates and the content features of their high-visibility tweets jointly shape message impact across six Spanish general elections, thereby clarifying the drivers of social media influence during electoral campaigns.Design/methodology/approach We analysed 22,573 tweets published by leading candidates between 2011 and 2023 in the 54 days preceding polling day, selecting the 50 most retweeted messages for each candidate and election (n = 1,250). OLS regressions modelled the logarithm of retweets and likes against governing or opposition status, ideological left-right axis, radical right affiliation, categorisation as traditional or new political force, negativity of the message, emotional tone, multimedia contents and inclusion of verifiable data, controlling for electoral cycle.Findings Impact rises significantly for newcomers, radical right actors and emotionally charged tweets, but falls for opposition leaders and video-based messages. Contrary to prevailing assumptions, negative rhetoric depresses likes while links or images do not foster impact. Tweets embedding objective performance data show a modest, albeit inconsistent, uplift in retweets. Overall, political variables explain more variance than content features, underscoring the continuing relevance of the party context in the digital arena.Originality/value Drawing on 12 years of election campaign data, this study integrates the political and content determinants of tweet impact in a multiparty European setting over the long term. By testing the explanatory power of factual government data, it expands theory on transparency and accountability in contemporary electoral communication.Peer review The peer review history for this article is available at:
Purpose In the era of digital transformation, enterprise social media (ESM) has become a core infrastructure for contemporary teamwork. However, less is known about how it functions when teams face adversity. This study investigates how ESM communication visibility influences team resilience in digitally mediated workplaces. Drawing on communication visibility theory and conservation of resources theory, the study unpacks how message transparency and network translucence contribute to the development of team resilience under adversity. Design/methodology/approach Time-lagged survey data were collected from 346 members of Chinese project teams across three stages. Hierarchical regression and bootstrapping techniques were applied to test the hypotheses, along with a series of endogeneity and robustness checks. Findings Results show that message transparency enhances team resilience-adaptive capacity through knowledge integration, while network translucence enhances team resilience-efficacious belief through collective team identification. Both effects are fully mediated, with no direct impact on resilience outcomes. In addition, team reflexivity strengthens the positive effect of message transparency on knowledge integration, whereas information overload weakens the effect of network translucence on team identification. Originality/value This study enriches communication visibility theory by extending its scope from routine performance to resilience building under adversity and clarifying the differentiated mechanisms linked to distinct resilience dimensions. It also identifies boundary conditions that shape these effects, offering a more nuanced understanding of how ESM fosters resilient teams in volatile organizational landscapes.
Purpose This study aims to examine how anthropomorphic design cues in healthcare chatbots, specifically appearance and communication style, influence users' intention to adopt health information through perceived competence and perceived warmth in low-to moderate-risk health contexts. Design/methodology/approach Drawing on the persuasion knowledge model, elaboration likelihood model, stereotype content model and computers are social actors, we develop a research model and conduct two online experiments. Study 1 adopts a 2 × 2 between-subjects design with 352 participants to examine the effects of anthropomorphic appearance (with vs without human names and avatars) and communication style (task-oriented vs social-oriented) on users' adoption intention through perceived competence and warmth. Study 2 employs a 2 × 2 × 2 factorial design with 473 participants to validate the findings and examine the moderating roles of persuasion knowledge and health literacy. Findings The results indicate that anthropomorphic appearance enhances perceived competence and warmth. A task-oriented communication style increases perceived competence, whereas a social-oriented style enhances perceived warmth. Both perceived competence and warmth significantly increase users' adoption intention and mediate the effects of anthropomorphic appearance and communication style on adoption intention. Additionally, persuasion knowledge weakens the effects of anthropomorphic appearance but does not moderate the relationship between communication style and perceived warmth. Health literacy negatively moderates the relationship between perceived warmth and adoption intention, while positively moderating that between perceived competence and adoption intention. Originality/value This study extends existing research by simultaneously examining anthropomorphic appearance and communication style in healthcare chatbots and uncovering the underlying psychological mechanisms through which these cues influence users' adoption intention. Peer review The peer review history for this article is available at: Link to the website.
PurposeSince the widespread uptake of social media in the 2010s, research on emotion and sentiment in online sharing has grown rapidly across various fields. Yet, this expansion lacks standardized methods and shared concepts, resulting in fragmented evidence and even contradictory findings on the direction of these effects. No systematic synthesis across fields currently exists. This review fills that gap by offering the first comprehensive overview of findings, scope, and methodologies at a pivotal moment before large language models reshape this research landscape. Design/methodology/approachThe systematic review identified 136 studies from 1,181 search results retrieved via Web of Science and Scopus in accordance with the PRISMA guidelines. Given the heterogeneity of the studies, the synthesis is presented in narrative form. FindingsEmotions and sentiment, in general, increase the popularity of information across platforms. The effect is found most consistently for negative discrete emotions, such as anger, anxiety, sadness and fear. Positivity bias is often identified in health communication, while negativity bias is prevalent in political communication. Going forward, the field should focus on sampling across platforms, greater linguistic diversity, and analysis of visual material. Originality/valueThe systematic review provides the first synthesis of a rapidly expanding field relevant to scholars across disciplines. It identifies potential sources of variance in the results and highlights methodological heterogeneity and identifies paths for future research.
Purpose This study examines how different types of social media use for health risk information relate to individuals' corrective behavioral responses to misinformation. It also investigates how perceived others' responses to misinformation shape one's own.Design/methodology/approach Data were gathered through a two-wave online survey conducted in Taiwan during the COVID-19 pandemic. Analysis included lagged autoregressive path modeling for direct and mediation effects and ordinary least squares regression for moderation effects of perceived others' responses on individuals' own responses.Findings Results showed that while social media exposure and expression were both related to correction sharing and debunking indirectly through verification norms, only social media expression had a direct relationship with these two corrective behavioral responses. Compared to correction sharing, which primarily correlated with social media use and verification norms, debunking was associated with a combination of cognitive, affective, and normative factors, as well as social media use. Moreover, evaluations of others' risk perception moderated the relationship between individuals' own risk perception and positive emotions. The relationships between individuals' information insufficiency and correction sharing/debunking were contingent upon perceived others' information insufficiency.Originality/value This study advances understanding of risk-related social media use by contrasting the direct and indirect roles of exposure and expression in predicting corrective behavioral responses to misinformation. It also contributes to the literature by differentiating the motivational mechanisms underlying correction sharing and debunking, two related yet distinct corrective behaviors. Finally, it identifies which perceived others' responses to misinformation serve as boundary conditions moderating individuals' own responses.Peer review The peer review history for this article is available at: .
Purpose This study explores the unique aspects of gaming privacy by proposing a dual-factor model of privacy concerns: breadth (BPC) and depth (DPC). It aims to examine how privacy concerns in gaming differ from those in other online contexts and to provide explanatory insights into the factors associated with users' privacy perceptions and behaviors in entertainment-driven environments. Flow, defined as a state of deep immersion and engagement, is introduced as a moderating factor, shaping the relationships between privacy concerns and disclosure intentions within gaming contexts.Design/methodology/approach Two empirical studies were conducted. Study 1, a 2 & times;2 online experiment (N = 240), compared privacy concerns between utility-driven instant messaging applications and entertainment-driven games. Study 2 employed the Antecedent-Privacy Concern-Outcome model to validate the relationships among privacy concerns, perceived vulnerability, and information disclosure intentions (N = 766), with flow as a moderating factor.Findings Study 1 revealed that users generally exhibited lower privacy concerns in gaming contexts, though privacy cues can increase their DPC. Study 2 showed that gaming contexts encourage users to trade privacy for entertainment, with flow experiences amplifying this effect.Originality/value Theoretically, this study introduces a dual-factor privacy concerns framework, contributing to the understanding of gaming privacy and its formation. The study also provides a novel explanation for the privacy paradox by incorporating flow. Practically, it advises game developers to enhance privacy cues and transparency and recommends policymakers stabilize gaming privacy regulations to avoid confusion from frequent changes.Peer review The peer review history for this article is available at:
Purpose Information cues in online medical communities (OMCs) critically shape patients’ physician service adoption, yet their joined effects remain underexplored. Based on the elaboration likelihood model (ELM) and the service quality model, this study develops an extended adoption framework to examine (1) the relative effects of central-route cues (information quality and interaction quality) vs peripheral-route cues (electronic word-of-mouth, eWOM) and (2) their joint effects under balanced and imbalanced conditions. Design/methodology/approach Using archival data from Haodf.com, this study applies polynomial regression with response surface analysis (RSA) to capture the complex relationships among adoption cues. Findings Results show that eWOM exerts a significantly stronger positive effect on service adoption than interaction quality. When service quality and eWOM are balanced, adoption is higher when both are high than when both are low. Under imbalance, adoption is higher in the low service quality – high eWOM condition than in the high service quality – low eWOM condition. Originality/value This study advances understanding of patients’ service adoption in OMCs by revealing the asymmetric and joint effects of central- and peripheral-route cues, offering actionable implications for platform governance and physician service strategies.
Purpose As generative AI technologies increasingly mediate user interactions and services, trust in these systems has become a key determinant of user engagement and data-sharing behavior. This study investigates trust formation mechanisms driving users' willingness to disclose personal information to generative AI, identifying key trustworthiness dimensions and examining their impact on perceived trust and disclosure intention.Design/methodology/approach Two empirical studies were conducted. Study 1 employed exploratory and confirmatory factor analyses (N = 557) to develop a multidimensional trustworthiness scale, while Study 2 applied structural equation modeling (N = 251) to assess how these factors affect trust in AI and subsequent disclosure intention.Findings Six trustworthiness factors were identified under competence (intelligence, company reputation and technical security) and warmth (psychological security, responsibility and comfort) dimensions. Psychological security, responsibility and technical security significantly predicted users' trust in generative AI, which strongly influenced intention to disclose personal information.Originality/value By focusing on the multidimensional nature of AI trustworthiness, this study identifies key antecedents and psychological mechanisms underlying users' trust in generative AI and disclosure behavior. It contributes to the literature by developing and validating a reliable scale for measuring the trustworthiness of generative AI systems. The findings highlight that trust is shaped not only by technical factors such as technical security but also by perceived moral dimensions, including psychological security and responsibility, offering practical implications for designing AI systems that are both functionally robust and ethically reassuring.Peer review The peer review history for this article is available at:
Purpose Financial rewards alone do not explain individuals' motivations to join and contribute to communities. In this article, we examine how identity shapes their innovation outcomes. We conceptualise identity as both a matter of positioning and a mechanism for creating a sense of belonging. Focusing specifically on software development as early inspirations for communities, the purpose of the article is to describe and discuss the role of identity in open-source software (OSS) innovations. Design/methodology/approach Data from four case studies were collected, including the perspectives of OSS communities, vendors and users. The various perspectives help to capture how a community is nested into its context and governance. Findings The article concludes that the community either has its primary function of providing an OSS aura to the OSS vendor, or its focus is on attracting developers and thereby contributing to the innovativeness of the OSS community. OSS community identities are mainly self-reflective, but also help to create rules of the community. Since it is the OSS vendor that communicates identities to external parties, the coherence and closeness between the OSS vendor and the community are important. Originality/value Through integrating literatures on organisational and branding identity, this article captures dual meanings across communities and contexts related to identity. It introduces the concepts of co-identity and spill-over identity to describe the relationship between communities and vendors as they seek to attract and retain contributors and users. Practically, the article highlights how communities should best be organised and promoted to remain innovative.
PurposeThe literature has revealed various factors driving misinformation sharing in the online sphere. However, there has been a lack of research on the structural factors that impact the spread of misinformation, and the specific roles played by social bots in this context remain largely unexplored.Design/methodology/approachUsing a social network approach, we analyzed a backbone network of co-sharing among Twitter (now X) accounts connected by sharing the same links from low-credibility news websites, constructed from 146,580 tweets.FindingsOur findings reveal that accounts with varying bot likelihoods are more likely to connect, supporting bot-based heterogeneity over homophily. The co-sharing network was also affected by structural factors, such as the tendency for popular accounts to attract more connections (known as preferential attachment), and individual account characteristics. The "echo chamber" hypothesis was not supported in the context of misinformation co-sharing.Originality/valueThese results highlight the significant impact of social bots in spreading misinformation.Peer reviewThe peer review history for this article is available at:
Purpose The growing number of social media influencers (SMIs) and heightened market competition challenge social media marketers to retain followers and attract new ones. While passionate love is essential for building long-term relationships early on, the literature rarely examines how SMIs cultivate followers' passionate love for them. Drawing on the similarity-attraction, self-congruity, and self-categorization theories, this study examines how multidimensional self-congruity influences followers' identity and passionate love for SMIs. Design/methodology/approach Online surveys were administered, data on 440 SMI followers were collected, and structural equation modeling was applied to test the hypotheses. Findings The results showed that followers feel passionate love for SMIs whose traits align with their actual self, ideal self, social self, and ideal social selves. Specifically, when followers see an image of an SMI that aligns with their actual or ideal selves, it strengthens their self-identity. Similarly, when they perceive an image of an SMI that fits their social or ideal social selves, it reinforces their social identity. Additionally, both self-identity and social identity positively influence followers' passionate love for SMIs. Originality/value The findings clarify how self-congruity shapes follower identity and passionate love for SMIs. They also offer valuable insights for SMI marketers by showing how SMI–follower congruity can be strategically leveraged to cultivate follower identity and passionate love. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2025-0092.
PurposeThis study aims to investigate how perceptions of a source's credibility influence individuals' willingness to share misinformation in digital communication contexts, particularly within private messaging environments. It aims to clarify why ordinary users, rather than malicious actors, often contribute to the spread of false content.Design/methodology/approachAcross three controlled experiments (total n = 914), we manipulated source credibility and measured participants' intentions to share false information. Mediation and moderation analyses assessed the roles of perceived message truthfulness and perceived social relevance to others.FindingsResults show that higher perceived source credibility increases the intention to share misinformation by enhancing perceived message truthfulness. Furthermore, the effect is stronger when messages are perceived as socially relevant, suggesting that individuals are more likely to share misinformation when it feels meaningful to their social circles.Research limitations/implicationsAlthough the studies rely on experimental manipulations rather than field data, they offer strong internal validity and open new avenues for investigating interpersonal credibility in closed digital networks.Practical implicationsFindings can inform interventions aimed at reducing misinformation sharing by addressing perceived trustworthiness and emphasizing message verification within social contexts.Originality/valueThis research contributes to the misinformation literature by experimentally testing interpersonal source credibility, mirroring real-world digital interactions. It introduces social relevance for others as a novel motivational factor beyond self-relevance, and it integrates perceptual, cognitive and social mechanisms into a unified explanatory framework.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2025-0900.
PurposeThis study synthesizes fragmented and interdisciplinary research on group polarization in social media through a systematic literature review, identifying key antecedents, mechanisms, consequences, and directions for future research.Design/methodology/approachUsing a multilevel analytical framework, we reviewed 1,201 high-impact publications from the Web of Science and Scopus databases. Bibliometric analysis was conducted using CiteSpace, and thematic synthesis was performed with the R package Bibliometrix to examine temporal trends, disciplinary clusters, and keyword evolution.FindingsThe review identifies three major categories of antecedents of group polarization: the information environment, individual characteristics, and the social environment. Core mechanisms, including selective exposure, consensus pressure, and reduced information diversity, intensify polarization by reinforcing homogeneous networks and weakening moderating influences. The consequences are wide-ranging, encompassing increased intergroup hostility, distorted public discourse, and growing challenges to governance and democratic processes.Research limitations/implicationsThe multidisciplinary nature of the literature, with diverse analytical perspectives, complicates the development of a fully unified framework and may constrain the generalizability of the findings.Practical implicationsPlatforms can adopt context-sensitive recommendation systems that gradually increase viewpoint diversity to counter selective exposure and consensus pressure. Platforms and policymakers should coordinate to mitigate polarization risks.Originality/valueThis study proposes an integrative framework that consolidates fragmented knowledge and advances understanding of the sociotechnical dynamics shaping digital discourse.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2025-0078
PurposeSocial media influencers can exert considerable persuasive impact among their followers. This study aims to explore whether this impact will be undermined once followers recognize the presence of sponsorship in influencers' persuasive messages, by examining the moderating effects of sponsorship awareness (SA) on follower purchase behaviors (PB), which impact the underlying processes of source credibility (SC), parasocial relationships (PSRs) and follow length (FL).Design/methodology/approachA survey was distributed through a collaboration with a YouTube influencer (N = 494) among her 74K followers. The mediation and moderation analyses were performed using Hayes PROCESS Modeling in SPSS.FindingsThe results indicate that SA negatively moderates the influence of FL on perceived influencer credibility and on PSRs, which sequentially impact purchase behaviors (PB).Practical implicationsThis research provides a strategic direction for influencer professional development. Influencers should prioritize publishing professional reviews and transparently disclosing sponsorships. Additionally, the impact mechanisms identified in this study help explain why some top-tier influencers may yield weaker promotional results. When selecting influencers for sponsored promotions, brands should evaluate the strength of these parasocial connections and followers' perceived influencer credibility.Originality/valueThis study expands the current understanding of influencer promotional communication in the context of follower stickiness and sponsorship disclosure. It is recommended that brands and social media creators develop thoughtful and innovative approaches to communicating sponsorship disclosures in ways that preserve the influencer's perceived credibility.
Purpose This study maps the evolution and intellectual structure of LinkedIn-related scholarship and situates it within the broader framework of online professional information behavior (OPIB). Design/methodology/approach A bibliometric analysis of 876 publications indexed in the Web of Science Core Collection (2000–2026) was conducted using VOSviewer and Bibliometrix. Co-authorship, co-citation, and keyword co-occurrence analyses were employed to examine collaboration patterns, knowledge foundations and thematic configurations. Findings LinkedIn research demonstrates sustained growth and increasing international collaboration. Co-citation analysis identifies three major research paradigms: user behavior and technology application, organizational use and career development and strategic management and digital transformation. Keyword clustering further reveals seven thematic areas, ranging from platform technology and data science to professional identity construction, online social capital and organizational diversity. Thematic evolution shows a shift from functional recruitment concerns toward identity-oriented and structurally embedded analyses, and more recently toward algorithmic governance and technologically mediated professional behavior. Research limitations/implications Despite reliance on a single database, this study offers clear theoretical and practical implications for OPIB. Theoretically, the findings clarify how social cognitive theory and self-determination theory shape research on professional identity and signaling, contributing to conceptual consolidation within OPIB. Practically, the results support more transparent recruitment practices by highlighting algorithmic evaluation and potential bias in platform-mediated hiring. Originality/value This study provides a comprehensive bibliometric overview of LinkedIn-related research, offering a quantitative mapping of scholarly discourse on OPIB. The findings serve as a reference point for future interdisciplinary research and theoretical development. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2025-0555
PurposeFact-checks have emerged as tools to correct misinformation, with mainly experimental research demonstrating their positive effects. Additionally, the main focus of fact-check studies lies on specific knowledge correction, while fact-checkers' democratic goals go beyond that. This study accommodates these methodological and conceptual limitations by investigating whether fact-checks can contribute to political knowledge (current affairs knowledge and contested issue knowledge).Design/methodology/approachThe study relies on a three-wave panel (N = 2.214). Respondents ranged between 16 and 30 years old and data were gathered during the Belgian elections.FindingsThe results show that both exposure to and subsequent consumption of fact-checks are positively related to current affairs knowledge and contested issue knowledge on the between-person level. This means that people who generally see and read with fact-checks more often tend to have higher knowledge overall. On the within-person level, relationships between exposure and reading and knowledge effects were less straightforward. The irregular relationships suggest that short-term changes in fact-check exposure and reading do not consistently translate into knowledge gains. These results suggest that the relationship between exposure and reading of fact-checks and knowledge differs more between individuals over time than it does within one individual.Originality/valueThis study is one of the first to investigate fact-check exposure effects over a longer period of time, relying on panel data. Additionally, by going beyond specific fact-check knowledge and relying instead on more general measures of political knowledge, this study contributes to the current fact-checking literature by bridging the desired goals of fact-check organizations and potential knowledge outcomes.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2025-0841
PurposeDeepfakes, the synthetic media generated using artificial intelligence to convincingly depict events that never actually occurred, pose a significant threat to society, yet we still lack efficient and effective countermeasures. While scholars have placed great hope in deepfake priming as a means to combat deepfakes, its effectiveness remains contested and superficial. The nuanced effects of deepfake priming are understudied, particularly regarding how it affects individuals' resilience to deepfakes across media. Therefore, this study examines the interactive effects of deepfake priming and the medium through which deepfakes are delivered on individuals' cognitive and behavioral responses to deepfakes.Design/methodology/approachWe employed an online between-subject experimental design involving 298 US adults. The sample was recruited through a reputable online panel provider, Qualtrics, to ensure a diverse, demographically representative sample. Participants were randomly assigned to one of four experimental conditions in a 2 (deepfake priming vs. no priming) & times; 2 (news website vs. social media) factorial design. Then, we assessed their belief in the authenticity of the deepfake video and their intention to share it.FindingsWe find that priming significantly reduces the intention to share deepfakes but does not enhance the capability to identify them. The medium through which deepfakes are delivered (news website vs social media) does not moderate deepfake priming's influence on either belief in deepfakes or intent to share deepfakes.Originality/valueThis study is among the first to examine the contextual influence of media platforms on deepfake intervention. It enhances the understanding of the deepfake priming effect by exploring the intricate interplay between priming and platforms delivering deepfakes. Practically, it sheds light on developing tailored deepfake interventions and maintaining online information trust and engagement.
