Work place: School of Computing and Creative Technologies, University of the West of England, Bristol, UK
E-mail: Faryad2.Bigdeli@live.uwe.ac.uk
Website:
Research Interests:
Biography
Faryad Bigdeli is a recent graduate with a Master’s degree in Data Science, specializing in machine learning and natural language processing. With a solid foundation in data analysis and model development, he has focused on addressing the challenges of fake review detection in e-commerce platforms. In his research, he explored the effectiveness of various machine learning models in detecting fake reviews across different datasets. His work highlights the practical implications of integrating machine learning models into real-time review monitoring systems to enhance the detection of fraudulent reviews while preserving consumer trust. Faryad Bigdeli is passionate about leveraging data science to create impactful solutions in the digital landscape and continues to pursue opportunities for research and application in this evolving field.
DOI: https://doi.org/10.5815/ijitcs.2025.03.04, Pub. Date: 8 Jun. 2025
This project addresses the growing issue of fake reviews by developing models capable of detecting them across different platforms. By merging five distinct datasets, a comprehensive dataset was created, and various features were added to improve accuracy. The study compared traditional supervised models like Logistic Regression and SVM with deep learning models. Notably, simpler supervised models consistently outperformed deep learning approaches in identifying fake reviews. The findings highlight the importance of choosing the right model and feature engineering approach, with results showing that additional features don’t always improve model performance.
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