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FRD-LSTM: a novel technique for fake reviews detection using DCWR with the Bi-LSTM method

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Abstract

The growth of the internet and the availability of online stores has increased the trend of online shopping among customers. People preferred to read the comments posted by potential buyers before purchasing a product. However, online stores are using machine learning (ML)-based approaches to generate fake comments about the product with the intention of either creating a false positive impact about their products or hitting the reputations of competitors by posting negative comments about their products. Therefore, it is crucial to classify real and fake reviews from online stores to save customers from fraud. To overcome these challenges, we have presented a deep learning-based approach namely FRD-LSTM to timely recognize fake reviews. After performing the preprocessing step, the deep contextualized word representation (DCWR) approach is applied to compute the deep features. Then, the principal component analysis (PCA) approach is applied to minimize the feature space. Finally, the Bi-LSTM classifier is trained on the computed features to classify the real and bogus reviews. Our method improves the fake reviews classification performance while decreasing both the training and testing time complexity. We have tested our approach on a challenging dataset namely the Amazon product reviews database and attained an average accuracy value of 97.21%. We have confirmed through extensive experimentation that our approach is proficient to detect bogus reviews and can assist online buyers in protecting them from fake products.

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Data availability

We have used standard dataset which is publicly available.

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Authors and Affiliations

  1. Department of Software Engineering, UET Taxila, Taxila, Pakistan

    Huma Qayyum & Marriam Nawaz

  2. Department of Computer Science, UET Taxila, Taxila, Pakistan

    Farooq Ali

  3. Faculty of Computing, Riphah International University Gulberg Greens Campus, Islamabad, Pakistan

    Tahira Nazir

Authors
  1. Huma Qayyum
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  2. Farooq Ali
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  3. Marriam Nawaz
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  4. Tahira Nazir
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Correspondence to Tahira Nazir.

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Qayyum, H., Ali, F., Nawaz, M. et al. FRD-LSTM: a novel technique for fake reviews detection using DCWR with the Bi-LSTM method. Multimed Tools Appl 82, 31505–31519 (2023). https://doi.org/10.1007/s11042-023-15098-2

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  • DOI: https://doi.org/10.1007/s11042-023-15098-2

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