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Health-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM).

The authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model.

The research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3).

The authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.

Fact-checking is a process of seeking and displaying facts to confirm or counter uncertain information, which reduces the spread of fake news. However, little is known about how to promote fact-checking posts to online users on social media. Through uncertainty reduction theory and message framing, this first study examines the effect of fact-checking posts on social media with an avatar on online users' trust, attitudes, and behavioral intentions. The authors further investigate the congruency effects between promotional message framing (gain/loss/neutral) and facial expressions of the avatar (happy/angry/neutral) on online users' trust, attitudes, and behavioral intentions in the second study.

The authors conducted two studies and statistically analyzed 120 samples (study 1) and 519 samples (study 2) from Facebook users.

Results showed that including the neutral facial expression avatar in fact-checking posts leads to online users' greater trust and more positive attitudes. Furthermore, the congruency effects between loss message framing and the angry facial expression of the avatar can effectively promote online users' trust and attitudes as well as stronger intentions to follow and share.

This study offers theoretical implications for fact-checking studies, and practical implications for online fact-checkers to apply these findings to design effective fact-checking posts and spread the veracity of information on social media.

This paper aims to explain how consumer persuasion knowledge and perceived deception in advertisements can influence consumers’ future evaluation of fake news about a brand.

This research develops a conceptual model using widely used persuasion knowledge theory and confirmation bias theory. A questionnaire-based online survey (n = 410) was conducted by displaying an advertisement stimulus followed by a fake news stimulus to test the model. Covariance-based structural equation modeling was used to analyze the hypothesized research model.

The results demonstrate that consumers with high persuasion knowledge are more likely to trust and adopt fake news about an advertised brand through the mediation of perceived deception in the advertisement. Additionally, perceived deception indirectly affects information adoption through the mediation of news credibility.

Theoretically, this study contributes to the existing body of literature on advertising deception and fake news. This research also extends theory of persuasion knowledge in understanding adoption of fake news. Practically, this study has significant implications for various stakeholders, including brands, social media corporations and consumers.

This research adds novel insights in the relationship of consumers’ persuasion knowledge and credibility and adoption of fake news. Furthermore, the investigation of the relationship between the perceived deception in advertising and the adoption of fake news has not been explored, which is also novel.

The purpose of this paper is to examine the factors that significantly affect the prediction of fake news from the virality theory perspective. The paper looks at a mix of emotion-driven content, sentimental resonance, topic modeling and linguistic features of news articles to predict the probability of fake news.

A data set of over 12,000 articles was chosen to develop a model for fake news detection. Machine learning algorithms and natural language processing techniques were used to handle big data with efficiency. Lexicon-based emotion analysis provided eight kinds of emotions used in the article text. The cluster of topics was extracted using topic modeling (five topics), while sentiment analysis provided the resonance between the title and the text. Linguistic features were added to the coding outcomes to develop a logistic regression predictive model for testing the significant variables. Other machine learning algorithms were also executed and compared.

The results revealed that positive emotions in a text lower the probability of news being fake. It was also found that sensational content like illegal activities and crime-related content were associated with fake news. The news title and the text exhibiting similar sentiments were found to be having lower chances of being fake. News titles with more words and content with fewer words were found to impact fake news detection significantly.

Several systems and social media platforms today are trying to implement fake news detection methods to filter the content. This research provides exciting parameters from a viral theory perspective that could help develop automated fake news detectors.

While several studies have explored fake news detection, this study uses a new perspective on viral theory. It also introduces new parameters like sentimental resonance that could help predict fake news. This study deals with an extensive data set and uses advanced natural language processing to automate the coding techniques in developing the prediction model.

The spread of fake news represents a serious threat to consumers, companies and society. Previous studies have linked emotional arousal to an increased propensity to spread information and a decrease in people’s ability to recognize fake news. However, the effect of an individual’s emotional state on fake news sharing remains unclear, particularly during periods of severe disruptions such as pandemics. This study aims to fill the gap in the literature by elucidating how heightened emotions affect fake news sharing behavior.

To validate the conceptual model, this study uses a quantitative approach. Data were collected from 212 online questionnaires and then analyzed using the structural equation modeling technique.

Results of this study show that positive emotions have indirect effects on fake news sharing behavior by allowing users to view the quality of information circulating on social media in a more positive light, and increasing their socialization behavior leading them to share fake news. Negative emotions indirectly impact fake news sharing by affecting users’ information overload and reinforcing prior beliefs, which in turn increases fake news sharing.

This study identifies several novel associations between emotions and fake news sharing behavior and offers a theoretical lens that can be used in future studies. It also provides several practical implications on the prevention mechanism that can counteract the dissemination of fake news.

This study investigates the impact of individuals’ emotional states on fake news sharing behavior, and establishes four user-centric antecedents to this sharing behavior. By focusing on individuals’ emotional state, cognitive reaction and behavioral response, it is among the first, to the best of the authors’ knowledge, to offer a multidimensional understanding of individuals’ interaction with news that circulates on social media.

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.

Disinformation on social media is a serious issue. This study examines the effects of disinformation on COVID-19 vaccination decision-making to understand how social media users make healthcare decisions when disinformation is presented in their social media feeds. It examines trust in post owners as a moderator on the relationship between information types (i.e. disinformation and factual information) and vaccination decision-making.

This study conducts a scenario-based web survey experiment to collect extensive survey data from social media users.

This study reveals that information types differently affect social media users' COVID-19 vaccination decision-making and finds a moderating effect of trust in post owners on the relationship between information types and vaccination decision-making. For those who have a high degree of trust in post owners, the effect of information types on vaccination decision-making becomes large. In contrast, information types do not affect the decision-making of those who have a very low degree of trust in post owners. Besides, identification and compliance are found to affect trust in post owners.

This study contributes to the literature on online disinformation and individual healthcare decision-making by demonstrating the effect of disinformation on vaccination decision-making and providing empirical evidence on how trust in post owners impacts the effects of information types on vaccination decision-making. This study focuses on trust in post owners, unlike prior studies that focus on trust in information or social media platforms.

The post-millennial or Generation Z constitutes people born in 1997 or after. This study theorizes how news consumption habits of the post-millennial generation are reshaping the news. As the newest generation of media users, Generation Z or the post-millennials, comprising people born in 1997 or after, will inherit the millennial legacy. Generation Z has embraced the visual, verbal, and viral aspects of digital and social media platforms. They rarely engage with traditional news sources, which they deem as nearly extinct.

Based on 2019 meta-analytical research review of 16 key studies (published between 2017 and 2019) of media consumption habits of post-millennials, this research study delineates news consumption habits of post-millennials. It theorizes how this new generation of media users are embracing the visual, verbal, and viral media to reshape news content. The propensity of the post-millennials to participate in the news cycle shapes their rapidly changing preferences and usage patterns.

Over the years, news consumption has varied among different age groups. Newspapers and television were popular with the Silent generation, comprising people born between 1928 and 1945. The Internet significantly transformed media use among baby boomers, the generation born between 1946 and 1964, and Generation X, which constitutes people born between 1965 and 1980. The rise of social media has significantly transformed media use of millennials or Generation Y, born between 1981 and 1996. They were the first generation to come of age in the new millennium.

Unlike Generation X and boomers, the post-millennials or Generation Z sparsely engage with traditional news sources they deem as nearly extinct, including print media such as newspapers and magazines. They rarely watch television news or listen to radio. They report different news values with less concern about accuracy and more attention toward entertainment and interaction.

Fake news represents a real risk for brands, particularly for firms selling essential products, such as food items. Despite this anecdotal acknowledgement, the dynamics of the relationship between fake news and brand reputation remain under-explored. The present study addresses this gap by examining the association of consumer values (universalism and openness to change), brand trust, fake news risk and system trust in the context of natural food products.

The study utilised a cross-sectional survey design and the mall-intercept method to collect data from 498 consumers of natural food residing in India. To test the hypotheses, which were grounded in the stimulus-organism-response (SOR) framework, the collected data were analysed using covariance-based structural equation modelling in SPSS AMOS. The conceptual model proposed universalism and openness to change as stimuli, brand trust as an internal state or organism and fake news risk – captured through the tendency of consumers to believe and act on fake news – as a response.

The findings support a positive association of universalism with brand trust and a negative association with fake news risk. In comparison, openness to change has no association with either brand trust or fake news risk. Brand trust, meanwhile, is negatively related to fake news, and this association is moderated by system trust. Furthermore, brand trust partially mediates the relationship between universalism value and fake news risk.

Notably, the present study is one of the first attempts to understand the fake news risk associated with natural food brands by utilising the SOR framework in an emerging market setting. The study provides interesting insights for policymakers, brands and consumers.

Drawing on theoretical insights from the persuasion knowledge model (PKM), this study aims to propose and test a model that maps out the antecedents, process and consequences to explain how consumers process and respond to fake news about brands on Facebook.

Contextualizing the fake news about Coca-Cola’s recall of Dasani water, an online survey was conducted via Qualtrics with consumers in the USA (N  =  468). Data were analyzed using covariance-based structural equation modeling.

Results showed that self-efficacy and media trust significantly predicted consumers’ persuasion knowledge of the fake news. Persuasion knowledge of the fake news significantly influenced consumers’ perceived diagnosticity of the fake news and subsequent brand trust. Furthermore, persuasion knowledge of the fake news mediated the effects from self-efficacy on perceived diagnosticity of the fake news and brand trust, respectively.

This study contributes to the literature of brand management by examining how consumers process and respond to fake news about a brand. It also extends the persuasion knowledge model by applying it to the context of fake news about brands on social media, and incorporating antecedents (self-efficacy and media trust) and consequences (perceived diagnosticity and brand trust) of persuasion knowledge in this particular context. Practically, this study provides insights to key stakeholders of brands to better understand consumers’ information processing of fake news about brands on social media.