Artificial Intelligence based Framework for detecting Deceptive Online Reviews
Ms. Samruddhi P. Ingale1, Dr. V. H. Deshmukh2, Dr. P. P. Deshmukh3
1Student, Department of Computer Science and Engineering, PRMI&R, Badnera
2Professor, Department of Computer Science and Engineering, PRMI&R, Badnera
3Assistant Professor, Department of Computer Science and Engineering, PRMI&R, Badnera
Abstract - Online reviews play an important role in shaping customer decisions on digital platforms, but their reliability is often affected by the presence of deceptive reviews. These reviews are intentionally written to promote or demote products, which can mislead users and reduce trust in online systems. This paper presents a method for detecting fake reviews using a combination of natural language processing and machine learning techniques. The approach processes review text through standard preprocessing steps and extracts features based on term frequency–inverse document frequency, sentiment scores, and reviewer behavior patterns. Multiple classification models, including support vector machines, logistic regression, random forest, and deep learning methods, are evaluated for identifying deceptive content. Prior studies have shown that combining textual and behavioral features improves detection performance, as behavioral patterns often reveal inconsistencies not captured in text alone. In addition, machine learning models trained on structured features have demonstrated effectiveness in distinguishing genuine and fake reviews across different datasets. The proposed system also provides interpretable outputs to explain prediction results. Experimental observations indicate that integrating multiple feature types leads to more reliable classification compared to single-feature approaches, making the system suitable for practical use in online review platforms.
Key Words: Fake review detection, natural language processing, machine learning, sentiment analysis, opinion spam, text classification, behavioral analysis, feature extraction, deceptive reviews, explainable artificial intelligence
