Abstract: This paper provides a survey of recent research on the detection of fake online reviews using machine learning (ML) techniques. The rise of fake online reviews poses a significant challenge to the credibility of online review platforms, and detecting fake reviews is critical to ensure the integrity of these platforms.

The paper reviews different ML techniques, including supervised and unsupervised learning algorithms, hybrid approaches, and deep learning techniques, that have been used to detect fake online reviews. The review highlights the potential of these techniques and emphasizes the need for more robust and accurate models to combat the problem of fake reviews. Overall, the paper provides valuable insights into the ongoing research area of fake review detection using ML techniques.

PDF | DOI: 10.17148/IJARCCE.2023.12410

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