Master’s thesis at the faculty discussing the detection of fake reviews based on content mining using textual and behavioral features.

The Faculty of Computer Science and Mathematics, Department of Computer Science, discussed the Master’s thesis titled “Detection of Fake Reviews based on Content Mining using Textual and Behavioral Features” by the student Lina Shuja Abd Al-Zahra. The study aims to propose various methods and techniques as potential solutions to the problem of detecting fake reviews. These solutions include natural language processing, machine learning, and sentiment analysis. The proposed model’s accuracy in detecting fake reviews was improved by incorporating new behavioral variables. Word2vec model was utilized to encode text vectors, reducing processing complexity. Additionally, the Stack model was implemented using algorithms (MNB) and (GBA) for real-time classification of reviews in the Yelp dataset.
The proposed model demonstrated excellent performance with an accuracy of approximately 98% and an efficiency of 82% compared to related systems. The thesis was successfully accepted.