AI and machine learning-based techniques have shown promise in providing accurate predictions, but they still face a significant challenge in accounting for cultural, linguistic, and gender variations across different societies and populations.
A team of researchers from the University of Sharjah in the United Arab Emirates recently published their findings in the journal Expert Systems with Applications, where they conducted a thorough analysis of deception detection methods utilizing machine learning.
The study involved a comprehensive literature review, combing through databases like Google Scholar, Elsevier, ACM Digital Library, IEE Xplore, and Springer to gather relevant research papers published between 2012 and 2023. The objective was to extract insights from existing literature on deception detection and compare machine learning approaches with traditional methods.
The researchers identified 98 papers meeting their criteria, with a notable increase in publications from 2019 onwards. They aimed to provide a detailed overview of the field’s contributions and limitations, emphasizing the importance of accurate deception detection in understanding human behavior objectively.
