Enhancing Digital Marketing with AI: A Machine Learning Approach to Identify Fake Reviews on Amazon

Sara Ahsain (), Oumaima Louzar, M’hamed Ait Kbit and Yasyn El Yusufi
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Sara Ahsain: Abdelmalek Essaadi University, IABL, STSM Doctoral Center
Oumaima Louzar: Abdelmalek Essaadi University, IABL, STSM Doctoral Center
M’hamed Ait Kbit: Abdelmalek Essaadi University, IABL, STSM Doctoral Center
Yasyn El Yusufi: Abdelmalek Essaadi University, IABL, STSM Doctoral Center

A chapter in Technological Innovations for Sustainable Development, 2025, pp 301-313 from Springer

Abstract: Abstract The rapid growth of e-commerce platforms has led to an increasing reliance on customer reviews for purchasing decisions. However, the prevalence of fake reviews poses a significant challenge that undermines consumer trust and product ratings. This study addresses the issue of fake comments in Amazon product reviews by employing a comparative analysis of machine learning models like Support Vector Machines (SVM), Classification and Regression Trees (CART) and Multilayer Perceptron (MLP). Amazon reviews’ dataset was preprocessed through text normalization, feature extraction and also feature selection techniques (TF-IDF). These results demonstrate that SVM achieves the highest accuracy (90%) and specificity (92%), outperforming CART and MLP in detecting fake reviews.

Keywords: Fake Review Detection; Machine Learning; E-Commerce; Amazon Reviews; Classification (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-032-06725-8_26

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DOI: 10.1007/978-3-032-06725-8_26

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