Advanced Intelligent System For Website Review Analysis

Abstract:-The rise of digital marketplaces has transformed consumer decision-making, with online reviews playing a crucial role in shaping trust and influencing purchasing behavior. This paper examines sentiment analysis in e-commerce platforms, focusing on how review dynamics impact consumer perceptions. Our findings indicate that early reviewers tend to assign higher ratings, while previous reviewers often provide more lenient feedback, highlighting distinct rating trends over time. To systematically analyze consumer sentiments, we implemented sentiment classification at both the sentence and comment levels, effectively categorizing reviews into positive and negative sentiments. This approach enhances the reliability of feedback processing, enabling better organization of large volumes of usergenerated content. The results validate the effectiveness of our sentiment classification framework, demonstrating its role in improving the credibility and trustworthiness of online reviews. By addressing the challenges associated with review analysis, our research contributes to enhancing consumer trust and informed decision-making in digital marketplaces. Future work will explore advanced deep learning models to further improve sentiment prediction accuracy and capture nuanced emotions in textual feedback.

---