Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42116
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In the digital era, the internet has become an integral part of daily life, with people increasingly relying on it for various activities. The rise of social media platforms and blogs has further amplified internet usage, leading to a surge in user- generated content such as reviews and comments. These reviews are invaluable for businesses managing websites, offering insights for design improvements, personalization, and a deeper understanding of user preferences. Additionally, such feedback serves as a critical resource for other users seeking reliable information about websites. This paper proposes a framework that utilizes opinion mining and Generative AI (Gen AI) to evaluate websites by analyzing user reviews and ratings. The system not only extracts meaningful insights from feedback but also compares websites across different brands based on performance metrics and user satisfaction scores. By leveraging advanced AI techniques, it generates ratings and provides personalized recommendations to enhance the user experience. The primary objective of this approach is to ensure users have a seamless experience by helping them make informed decisions and identifying websites that align with their preferences. This framework also benefits businesses by delivering actionable insights for continuous improvement and competitive benchmarking, making it a robust tool for the evolving digital landscape.
KEYWORDS
Publication Date
6/2/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
1
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...