Abstract
The rapid development of artificial intelligence and the increase in the number of fake news spread on online social networks pose a global problem with harmful consequences. This study aimed to analyze the influence of various variables on the distribution of fake news on social media. The study comprised 275 participants and we analyzed the data using Partial Least Squares—Structural Equation Modeling (PLS-SEM). The study found that factors such as pass time, information sharing, social media fatigue, and self-disclosure play an important role in the distribution of fake news among users. However, altruism, socialization, information seeking, and online trust do not influence the distribution of fake news. The results have important implications for researchers, social media users, businesses, organizations, and governments, as fake news can affect any domain. Therefore, it is recommended to develop algorithms and technologies used by social media platforms to detect and remove false content, and to create educational programs to teach users to identify and report fake news.
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Acknowledgements
This work was funded by a grant of the Ministry of Research, Innovation and Digitization through Programmme 1—Development of the national research-development system, Subprogramme 1.2—Institutional performance—Projects to fund excellence in RDI, contract no. 21PFE/30.12.2021 code/ID PFE-550-UBB.
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Sterie, LG., Sitar-Tăut, DA., Mican, D. (2024). Analyzing the Antecedents of Fake News Sharing in Online Social Networks. In: Ciurea, C., Pocatilu, P., Filip, F.G. (eds) Proceedings of 22nd International Conference on Informatics in Economy (IE 2023). IE 2023. Smart Innovation, Systems and Technologies, vol 367. Springer, Singapore. https://doi.org/10.1007/978-981-99-6529-8_13
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