Fake news detection has emerged as a critical challenge in the modern information ecosystem, where the rapid proliferation of misinformation threatens democratic processes, public health, and societal stability. Machine learning (ML)-based approaches have demonstrated significant promise in automatically identifying and classifying misleading information across diverse platforms. This study presents a comprehensive scientometric and systematic review of ML-based fake news detection research, drawing on 649 peer-reviewed articles indexed in the Web of Science database (1991--2023). Using bibliometric tools including R-Bibliometrix and VOSviewer, we systematically evaluate publication trends,... More >