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Understanding individual susceptibility to political fake news is critical because fake news can target specific psychological profiles of vulnerable individuals. Consequently, this research examines five individual risk (i.e. susceptibility) and resilience (i.e. protective) factors, conspiracy mentality, patriotism, perceived threat to freedom, media literacy and concern for disinformation, to determine if they inform belief in political fake news and subsequently, to what degree belief impacts private engagement with political fake news.

Using a fictional political fake news stimulus, the authors conducted a deductive thematic analysis of 10 semi-structured interviews and an online survey of 722 United Kingdom (UK) citizens analysed using structural equation modelling.

Conspiracy mentality and patriotism were positively associated with belief in political fake news, while media literacy and concern for disinformation were negatively associated with belief in political fake news. Perceived threat to freedom was a strong theme in the qualitative data but had no statistical effect on belief in political fake news. Belief in political fake news was positively associated with further engagement with the fake news story, acting as a mediator in the model.

Distinct from previous research that focuses on partisanship and sharing behaviour, this research forwards a model underpinned by social identity theory to build an integrated understanding of political fake news belief. The results demonstrate that political identity motivations beyond partisanship are salient when examining individual susceptibility to political fake news and that belief in political fake news plays a core role in understanding subsequent private engagement with the story.

The purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users.

Tweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed.

The majority of the top 50 Twitter users are more likely to be automated bots, while certain users’ posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways.

The research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is.

This paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term “#fakenews” in connection to other news organizations, parties and related figures.

The purpose of this study is to examine the respondents’ evaluation of the pervasiveness of fake news through various SM platforms in Kuwait. The authors also examined the respondents’ attitudes toward most fake news on SM. A total of 1,539 Kuwaitis were selected.

The questionnaire was the major tool for this study. The respondents, from whom demographic information was obtained, were asked about which SM platforms most frequently spread fake news, their attitudes toward the subjects most frequently involved in spreading fake news, their degree of use of the six SM platforms and interest in various subjects, and the attitudes toward the negative nature of SM news. SPSS was used for the data analysis.

The results showed that WhatsApp was the most likely to be used to disseminate fake news; Twitter and Instagram ranked second. The younger subjects were affected more by text and voice clips than the older ones.

The study, hopefully, produces new knowledge on the subject of fake news in social media, especially in the Arab world, since there are few studies conducted in the region. The study showed that WhatsApp was the SM tool most likely to be responsible for disseminating fake news in Kuwait, which may shed light on the usage of this application to be a news tool, rather than merely an interpersonal communication medium.

The extensive distribution of fake news on the internet (FNI) has significantly affected many lives. Although numerous studies have recently been conducted on this topic, few have helped us to systematically understand the antecedents and consequences of FNI. This study contributes to the understanding of FNI and guides future research.

Drawing on the input–process–output framework, this study reviews 202 relevant articles to examine the extent to which the antecedents and consequences of FNI have been investigated. It proposes a conceptual framework and poses future research questions.

First, it examines the “what”, “why”, “who”, “when”, “where” and “how” of creating FNI. Second, it analyses the spread features of FNI and the factors that affect the spread of FNI. Third, it investigates the consequences of FNI in the political, social, scientific, health, business, media and journalism fields.

The extant reviews on FNI mainly focus on the interventions or detection of FNI, and a few analyse the antecedents and consequences of FNI in specific fields. This study helps readers to synthetically understand the antecedents and consequences of FNI in all fields. This study is among the first to summarise the conceptual framework for FNI research, including the basic relevant theoretical foundations, research methodologies and public datasets.

The broader analytical framing of systematically distorted communication (SDC) helps extract value out of the enormous amount of scholarship on fake news.

The massive literature on fake news has been the subject of handbook overviews, systematic literature reviews, summaries, taxonomies, citation studies and so on. Deploying these tools, the approaches that the literature takes can be characterized, Habermas' concept of systematically distorted communication (SDC) will then be presented in its context, reviewed and put to work to frame fake news research to tell us new things that individual pieces of specific analysis and research do not. Conclusions will be offered from this analysis.

Fake news research has become repetitive, revolving around themes such as the fate of journalism, the role of technology, remediating its effects and deep dives into definitional components (disinformation, misinformation, lies and so on). A broader framing of systematically distorted communication allows us to arrive at some conclusions about contemporary fake news: that it is a power strategy with a particular right-wing slant and it creates a sociology – that is, its own interpretive environment – hostile to democratic functioning. It answers the question: what is fake news for?

A perspective on fake news research is much needed and Habermas' concept is a useful framing mechanism for the large corpus of research. Systematically distorted communication asks – and answers – different questions of the research. Meanwhile, SDC itself is modified by its application to fake news research and contemporary conditions.

This paper aims to explore the determinants causing fake information proliferation on social media platforms and the challenges to control the diffusion of fake news phenomena.

The authors applied the systematic review methodology to conduct a synthetic analysis of 37 articles published in peer-reviewed journals retrieved from 13 scholarly databases.

The findings of the study displayed that dissatisfaction, behavior modifications, trending practices to viral fake stories, natural inclination toward negativity and political purposes were the key determinants that led individuals to believe in fake news shared on digital media. The study also identified challenges being faced by people to control the spread of fake news on social networking websites. Key challenges included individual autonomy, the fast-paced social media ecosystem, fake accounts on social media, cutting-edge technologies, disparities and lack of media literacy.

The study has theoretical contributions through valuable addition to the body of existing literature and practical implications for policymakers to construct such policies that might prove successful antidote to stop the fake news cancer spreading everywhere via digital media. The study has also offered a framework to stop the diffusion of fake news.

The insidious proliferation of online misinformation represents a significant societal problem. With a wealth of research dedicated to the topic, it is still unclear what determines fake news sharing. This paper comparatively examines fake and accurate news sharing in a novel experimental setting that manipulates news about terrorism.

The authors follow an extended version of the uses-and-gratification framework for news sharing, complemented by variables commonly employed in fake news rebuttal studies.

Logistic regression and classification trees revealed worry about the topic, media literacy, information-seeking and conservatism as significant predictors of willingness to share news online. No significant association was found for general analytical thinking, journalism skepticism, conspiracy ideation, uses-and-gratification motives or pass-time coping strategies.

The current results broaden and expand the literature examining beliefs in and sharing of misinformation, highlighting the role of media literacy in protecting the public against the spread of fake news.

This is, to the authors’ knowledge, the first study to integrate a breadth of theoretically and empirically driven predictors of fake news sharing within a single experimental framework.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2022-0693

Deepfakes are fabricated content created by replacing an original image or video with someone else. Deepfakes have recently become commonplace in politics, posing serious challenges to democratic integrity. The advancement of AI-enabled technology and machine learning has made creating synthetic videos relatively easy. This study explores the role of political brand hate and individual moral consciousness in influencing electorates' intention to share political deepfake content.

The study creates and uses a fictional deepfake video to test the proposed model. Data are collected from N = 310 respondents in India and tested using partial least square–structural equation modelling (PLS-SEM) with SmartPLS v3.

The findings support that ideological incompatibility with the political party leads to political brand hate, positively affecting the electorates' intention to share political deepfake videos. This effect is partially mediated by users' reduced intention to verify political deepfake videos. In addition, it is observed that individual moral consciousness positively moderates the effect of political brand hate on the intention to share political deepfake videos. Intention to share political deepfake videos thus becomes a motive to seek revenge on the hated party, an expression of an individual's ideological hate and a means to preserve one's moral self-concept and strengthen their ideologies and moral beliefs.

The study expands the growing discussion about disseminating political deepfake videos using the theoretical lens of the negative consumer-brand relationship. It validates the effect of political brand hate on irrational behavior that is intended to cause harm to the hated party. Further, it provides a novel perspective that individual moral consciousness may fuel the haters' desire to engage in anti-branding behavior. Political ideological incompatibility reflects ethical reasons for brand hate. Therefore, hate among individuals with high moral consciousness serves to preserve their moral self.

This paper aims to unify fragmented definitions of fake news and also present a comprehensive classification of the concept. Additionally, it provides an agenda for future marketing research based on the findings.

A review of 36 articles investigating fake news from 1990 to 2020 was done. In total, 615 papers were found, and the article pool was refined manually in two steps; first, articles were skimmed and scanned for nonrelated articles; second, the pool was refined based on the scope of the research.

The review resulted in a new definition and a collective classification of fake news. Also, the feature of each type of fake news, such as facticity, intention, harm and humor, is examined as well, and a definition for each type is presented.

This extensive study, to the best of the author’s knowledge, for the first time, reviews major definitions and classification on fake news.

Este artículo pretende unificar las definiciones fragmentadas de las noticias falsas y también presentar una clasificación exhaustiva del concepto. Además, ofrece una agenda para futuras investigaciones de marketing basada en los resultados.

Se realizó una revisión de 36 artículos que investigaban las noticias falsas desde 1990 hasta 2020. Se encontraron 615 artículos, y el grupo de artículos se refinó manualmente en dos pasos, primero, se descremaron los artículos y se escanearon los artículos no relacionados, segundo, el grupo se refinó basado en el alcance de la investigación.

La revisión dio como resultado una nueva definición y una clasificación colectiva de las noticias falsas. Además, se examinan las características de cada tipo de noticias falsas, como la facticidad, la intención, el daño y el humor, y se presenta una definición para cada tipo.

este amplio estudio revisa por primera vez las principales definiciones y la clasificación de las noticias falsas.

本文旨在统一假新闻的零散定义, 并对假新闻的概念进行全面的分类。此外, 它还根据本文的研究结果为未来的营销研究提供了一个议程。

对1990年至2020年期间调查假新闻的36篇文章进行了回顾。一共发现了615篇论文, 并分为两步对此文章库进行了人工提炼：首先, 对文章进行略读和扫描以找出非相关文章, 其次, 根据研究范围对文章库进行了提炼。

此次审查导致了对假新闻的新定义和集体分类。此外, 还分析了假新闻的真实性、意图、危害性、幽默性等各种类型的特征, 并给出了各种类型的定义。

此项涉及广泛假新闻内容的研究首次回顾了关于假新闻的主要定义和分类。