Скачать или смотреть VERSA: Validating Evaluations with a Robust Scoring Approach - Detecting Fake Reviews through MRCS

Authors: Mohammed Ennaouri, Ahmed Zellou (BEEI 8288)
In the digital age, online commerce has grown, and as a result, consumers now rely more than ever on other consumer feedback. But as the value of reviews increased, so did fake ones, which are now infecting platforms and influencing users' perceptions. The widespread use of fake reviews undermines the trust essential to online marketplaces, posing an increasing challenge. This study addresses the difficulty of identifying fake reviews by introducing a distinctive methodology that incorporates advanced Natural Language Processing (NLP) tools. The study provides comprehensive explanations on how Word2Vec contributes to semantic diversity in review analysis. We explore the semantic environment by including a new metric and provide a normalized textual similarity measure necessary for accurate detection. Furthermore, the inclusion of an exaggeration detection technique enhances the model's ability to recognize deceptive variations in reviews' form. Furthermore, adaptive clustering differs from traditional K-means clustering in that it alters clusters to adjust the constant evolution of misleading linguistic patterns. Empirical validation on the Yelp Labeled Dataset demonstrates the accuracy of the approach and identifies areas for further development. Metrics such as precision, recall, and F1 score shed light on the model's performance.

Bulletin of Electrical Engineering and Informatics
https://beei.org

Supported by Master Program of Electrical and Computer Engineering, Universitas Ahmad Dahlan, https://mee.uad.ac.id #yogyakarta
Admission: https://mee.uad.ac.id/pendaftaran/

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