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

In: Technological Innovations for Sustainable Development

Author

Listed:
  • 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)

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.

Suggested Citation

  • Sara Ahsain & Oumaima Louzar & M’hamed Ait Kbit & Yasyn El Yusufi, 2025. "Enhancing Digital Marketing with AI: A Machine Learning Approach to Identify Fake Reviews on Amazon," Lecture Notes in Information Systems and Organization, in: Badr-Eddine Boudriki Semlali & Ikram Ben Abdel Ouahab & Fabio Angeletti (ed.), Technological Innovations for Sustainable Development, pages 301-313, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-06725-8_26
    DOI: 10.1007/978-3-032-06725-8_26
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