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Social networking sites have become breeding grounds for the spread of fake news and misinformation. At the height of the Covid-19 pandemic, the spread of fake news intensified, causing complications for health communicators by drowning authentic information from verifiable official sources. Looking at the impact of this growing phenomenon on people’s attitudes and behaviour during the pandemic, research in the area must be populated to help governments, supranational organisations, non-governmental organisations as well as civil society organisations to formulate policies to curb the menace. This study was therefore undertaken to unravel current gaps and future research avenues to empower academia in achieving the desired scholarly impact.

The study adopted the systematic review approach, relying on 56 peer-reviewed articles on social media, fake news and misinformation in the Covid-19 pandemic.

The study found that the use of social media during the height of the pandemic led to unhelpful information creation and sharing behaviours such that people’s self-awareness reduced drastically, thereby impeding the fight against the pandemic. The study also established that Entertainment motives, Ignorance and Altruism motives were the dominant factors that influenced the spread of fake news. There was evidence of the marginalization of research on the subject matter from contexts such as Africa, South America and Oceania.

This study has established existing gaps in issues and evidence, methodology, theory and context and consequently discussed future research avenues for social media use and the spread of fake news. The study has also provided practical implications for both governmental and non-governmental organisations in curbing the phenomenon of fake news and misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2022-0366.

This study aims to investigate the current practices being implemented against the dissemination of fake online news, identify the relationship of new media literacy (NML) with fake news epidemic control and find out the challenges in identifying valid sources of information.

To accomplish constructed objectives of this study, a systematic literature review (SLR) was conducted. The authors carried out the “Preferred Reporting Items for the Systematic Review and Meta-analysis” guidelines as a research methodology. The data were retrieved from ten world’s leading digital databases and online tools. A total of 25 key studies published in impact factor (IF) journals were included for systematic review vis-à-vis standard approaches.

This study revealed trending practices to control fake news consisted of critical information literacy, civic education, new thinking patterns, fact-checkers, automatic fake news detection tools, employment of ethical norms and deep learning via neural networks. Results of the synthesized studies revealed that media literacy, web literacy, digital literation, social media literacy skills and NML assisted acted as frontline soldiers in combating the fake news war. The findings of this research also exhibited different challenges to control fake news perils.

This study provides pertinent theoretical contributions in the body of existing knowledge through the addition of valuable literature by conducting in-depth systematic review of 25 IF articles on a need-based topic.

This scholarly contribution is fruitful and practically productive for the policymakers belonging to different spectrums to effectively control web-based fake news epidemic.

This intellectual piece is a benchmark to address fake news calamities to save the social system and to educate citizens from harms of false online stories on social networking websites.

This study vivifies new vistas via a reinvigorated outlook to address fake news perils embedded in dynamic, rigorous and heuristic strategies for redefining a predetermined set of social values.

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.

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.

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.

This paper attempts to explain the infodemics that the coronavirus crisis has generated through the dissemination of fake news, which can lead people and institutions to make decisions that end up being counterproductive to their own interests or to the needs of society.

The existing literature in the field of information has been reviewed, as well as the fake news that has been spread during the COVID-19 crisis. Based on this review, a series of guidelines have been drawn up to enable citizens to detect the false information that is being disseminated.

This paper has established a series of recommendations to be followed by any communicator, journalist or person who creates content and information to promote effective communication during this crisis. It concludes that the role of the media is key in trying to reduce the spread of fake news.

This paper reflects the need to combat fake news originating during the pandemic through effective communication following a series of guidelines.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0352