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Context: The spread of fake news on social media platforms has emerged as a pressing concern in recent years. Between 2018 and 2023, numerous secondary studies (SS) have explored this issue, employing diverse methodologies and approaches. Surprisingly, no tertiary study exists to summarize the state of the research. Objective: The aim of this paper is to provide a rapid overview of the SS on fake news research topics for researchers and practitioners. Method: We defined and conducted a rapid tertiary review to find SS published from 2013 to August 2023. 50 most relevant studies in a Google Scholar search were retrieved, from which 15 secondary studies were included and analyzed. Results: A diversity of definitions for fake news exist, often associated with the technology and content in which they are being analyzed. Various stages of fake news processing are covered in the literature. A predominance in the use of deep learning (DL) was observed and challenges still remain, including the urgent need for real-time learning and early detection of fake news.
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Gomes et al. (2023) studied this question.