Social networking sites and social media serve as vital avenues of interaction among people all over the world as well as essential platforms for the distribution of information. Companies, like individuals, embrace social networks as a non-formal way to engage with their customers and suppliers, gather information about their online behavior, and offer personalized content. Both scholars and managers from various organizations looking to increase their competitive edge or market shares have an interest in the impact that social networks have on human behavior. Because of this, the current research seeks to investigate how users perceive a wide range of concepts related to using social networking sites, including fear of missing out (FoMO), social networking fatigue, information and communication overload, ubiquitous connectivity and peer communication, and privacy concerns. The authors also examined users’ intentions to continue using social networking sites despite the COVID-19 outbreak in order to ensure a more thorough understanding of the research topic. The findings aim to provide a better knowledge of how users see interaction on social networks in their daily lives as well as an overview of user perspectives on the terms mentioned above.

In the age of information technology, online social networks are part of our daily lives and are the main source of obtaining and transmitting information, which can be a blessing or a curse. Although social networks facilitate access to news and information, one issue remains of serious significance, namely the phenomenon of fake news. The short time of spreading fake news in the online social environment is the main cause for concern, and users' attitudes towards fake news can facilitate or reduce its spread. Therefore, the main objective of the current study is to perform an overall analysis of users' perceptions on the behavior and attitudes toward distributing fake news through social networks. To ensure a comprehensive interpretation of the research topic, we analyzed both the reasons behind the behavior of distributing fake news and the active or passive actions that users apply in relation to them. As verifying the authenticity of the source is an essential component of the preventive behavior of fake information distribution, an analysis of the action was performed to verify the credibility of the sources among users. Therefore, the detailed and joint analysis of the above variables gives a note of originality to this study. In addition, the results of the study have significant practical implications for social platforms and are intended to provide a better understanding of how online social network users perceive fake information and interact with it. More specifically, they can be used in the development of predictive models that have the role of automating the identification of fake news in the context of machine learning algorithms and big data.