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This study aims to understand the allure and danger of fake news in social media environments and propose a theoretical model of the phenomenon.

This qualitative research study used the uses and gratifications theory (UGT) approach to analyze how and why people used social media during the 2016 US presidential election.

The thematic analysis revealed people were gratified after using social media to connect with friends and family and to gather and share information and after using it as a vehicle of expression. Participants found a significant number of fake news stories on social media during the 2016 US presidential election. Participants tried to differentiate between fake news and real news using fact-checking websites and news sources and interacted with the social media users who posted fake news and became part of the echo chamber. Behaviors like these emerged in the analysis that could not be completely explained by UGT and required further exploration which resulted in a model that became the core of this study.

This is a small-scale exploratory study with eight diverse participants, findings should not be generalized to larger populations. Time-specific self-reporting of information from social media and fake news during the 2016 US presidential election. Upgrading public policies related to social media is recommended in the study, contributing to burgeoning policy discussions and provides recommendations for both purveyors of social media and public policymakers.

Upgrade in public policies related to social media is recommended in the study and contributes to burgeoning policy discussions and provides recommendations for both purveyors of social media and public policymakers.

Social media users are spending increased time on their preferred platforms. This study increases the understanding of the nature, function and transformation of virtual social media environments and their effects on real individuals, cultures and societies.What is original/of value about the paper?This exploratory study establishes the foundation on which to expand research in the area of social media use and fake news.

This exploratory study establishes the foundation to expand research in the area of social media use and fake news.

This paper aims to examine how content relevancy influences consumers’ preference to receive and share fake news. Further, it investigates how these receivers perceive the social image of the people who share fake news. Finally, this study examines how brand strength and valence and credibility of fake content influence consumer’s word-of-mouth recommendations, purchase intentions and attitude toward the brand.

Three experiments were conducted to test the hypotheses. The data was analyzed using a two-way analysis of variance and PROCESS techniques.

Findings indicate that people prefer to receive and share relevant content, even if it is fake. Sharing fake news conveys the sender’s sociability but also creates a negative perception of narcissism. Individuals are more likely to recommend a brand if the fake news is perceived as credible and positive (vs negative). Finally, brand-strength can help brands to negate the harmful effects of fake news.

Future research can explore the role of group dynamics, tie-strength and media richness (text, image and videos) in the dispersion of fake news and its impact on brands.

Marketers should communicate and educate consumers that sharing fake content can harm their social image, which can reduce information dispersion. Marketers should also improve brand-strength that can protect the brand against the adverse impact of fake news.

This study contributes to the emerging literature on fake news by studying the impact of fake news on consumer intentions and attitudes toward the brand, which are critical for the success of any brand.

The spread of fake news on social networking sites (SNS) poses a threat to the marketing landscape, yet little is known about how fake news affect consumers’ perceptions, attitudes and behaviors. This study aims to explore when consumers believe fake news, whom they blame for it (e.g. negative attitudes toward brands or SNS) and when they choose to share it.

Data obtained from 80 open-ended, semistructured interviews, conducted with SNS consumers and experts, is analyzed following the principles of grounded theory and the Gioia methodology.

Factors affecting consumers’ perceptions of fake news include skepticism, awareness, previous experience, appeal and message cues. Consumers’ brand- and SNS-related attitudes are affected by consumers’ blame, which is determined by consumers’ perceptions of the vetting efforts, role and ethical obligation of SNS. Consumers’ motives for sharing fake news include duty, retaliation, authentication and status-seeking. Theoretical and practical implications derived from the study’s novel conceptual framework are discussed.

This study identifies communication strategies that marketing professionals can use to mitigate and counter the negative effects of fake news.

By simultaneously considering consumers’ perceptions of the source, information and medium (i.e. SNS), this study presents a novel conceptual framework providing a marketing-centered, dynamic view on consumers’ fake news experience and connecting consumers’ perceptions, attitudes and behaviors in the context of fake news.

This paper presents recently published resources on library instruction and information literacy, providing an introductory overview and a selected annotated bibliography of publications covering various library types, study populations and research contexts.

This paper introduces and annotates English-language periodical articles, monographs, dissertations, reports and other materials on library instruction and information literacy published in 2020.

The paper provides a brief description of all 440 sources and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians, researchers and anyone interested in a quick and comprehensive reference to literature on library instruction and information literacy.

“Fake news” or misinformation sharing using social media sites into public discourse or politics has increased dramatically, over the last few years, especially in the current COVID-19 pandemic causing concern. However, this phenomenon is inadequately researched. This study examines fake news sharing with the lens of stimulus-organism-response (SOR) theory, uses and gratification theory (UGT) and big five personality traits (BFPT) theory to understand the motivations for sharing fake news and the personality traits that do so. The stimuli in the model comprise gratifications (pass time, entertainment, socialization, information sharing and information seeking) and personality traits (agreeableness, conscientiousness, extraversion, openness and neuroticism). The feeling of authenticating or instantly sharing news is the organism leading to sharing fake news, which forms the response in the study.

The conceptual model was tested by the data collected from a sample of 221 social media users in India. The data were analyzed with partial least squares structural equation modeling to determine the effects of UGT and personality traits on fake news sharing. The moderating role of the platform WhatsApp or Facebook was studied.

The results suggest that pass time, information sharing and socialization gratifications lead to instant sharing news on social media platforms. Individuals who exhibit extraversion, neuroticism and openness share news on social media platforms instantly. In contrast, agreeableness and conscientiousness personality traits lead to authentication news before sharing on the social media platform.

This study contributes to social media literature by identifying the user gratifications and personality traits that lead to sharing fake news on social media platforms. Furthermore, the study also sheds light on the moderating influence of the choice of the social media platform for fake news sharing.

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 presents recently published resources on library instruction and information literacy. It provides an introductory overview and a selected annotated bibliography of publications covering various library types, study populations and research contexts. The selected bibliography is useful to efficiently keep up with trends in library instruction for busy practitioners, library science students and those wishing to learn about information literacy in other contexts.

This article annotates 424 English-language periodical articles, monographs, dissertations, theses and reports on library instruction and information literacy published in 2021. The sources were selected from the EBSCO platform for Library, Information Science, and Technology Abstracts (LISTA), Education Resources Information Center (ERIC), Scopus, ProQuest Dissertations and Theses, and WorldCat, published in 2021 that included the terms “information literacy,” “library instruction,” or “information fluency” in the title, abstract or keywords. The sources were organized in Zotero. Annotations summarize the source, focusing on the findings or implications. Each source was categorized into one of seven pre-determined categories: K-12 Education, Children and Adolescents; Academic and Professional Programs; Everyday Life, Community, and the Workplace; Libraries and Health Information Literacy; Multiple Library Types; and Other Information Literacy Research and Theory.

The paper provides a brief description of 424 sources and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians, researchers and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy within 2021.

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.

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.

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.