Review Lens: AI-Powered Sentiment Analysis for Brand Comparison
Abstract
Review Lens is a sentiment analysis-based system that helps consumers make informed purchasing decisions. By analyzing customer reviews for up to three brands of a given product, it determines the best brand based on positive sentiment distribution. The system utilizes web scraping, NLP (VADER), and data visualization to provide insights through pie charts. This tool is valuable for e-commerce, businesses, and consumers, offering a data-driven approach to brand comparison. This system empowers users to make informed decisions by leveraging sentiment insights, offering a reliable, automated, and user-friendly tool for brand comparison and recommendation
References
Meizhen Hannah Zahirah, & Tri Widarmanti. (2022). Sentiment Analysis and Topic Modeling Study: The Comparison of Cosmetics Product Online Reviews. International Journal of Sciences: Basic and Applied Research (IJSBAR), 64(1), 50–65. Retrieved from https://www.gssrr.org/index.php/JournalOfBasicAndApplied/article/view/14579
Huwail J. Alantari, Imran S. Currim, Yiting Deng, Sameer Singh, An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews, International Journal of Research in Marketing, Volume 39, Issue 1, 2022, Pages 1-19, ISSN 0167-8116,
https://doi.org/10.1016/j.ijresmar.2021.10.011.
Jagdale, R. S., Shirsat, V. S., & Deshmukh, S. N. (2019). Sentiment analysis on product reviews using machine learning techniques. In Cognitive Informatics and Soft Computing: Proceeding of CISC 2017 (pp. 639-647). Springer Singapore.
Anant Bhardwaj, Pradyumn Pratap Singh, Astha Bharti, Apurva Singh Parihar, Sandeep Kaur, 2024, Social Media Sentiment Analysis for Brand Monitoring, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 13, Issue 10 (October 2024),
Jian Jin, Ping Ji, Rui Gu, Identifying comparative customer requirements from product online reviews for competitor analysis, Engineering Applications of Artificial Intelligence, Volume 49, 2016, Pages 61-73, ISSN 0952-1976,
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