• T.Phanisurya
• Mr. E. Rameshreddy

In the competitive landscape of e-commerce, customer reviews play a crucial role in influencingpurchasing decisions. Understanding and predicting the sentiment of these reviews can provide valuableinsights for businesses aiming to enhance customer satisfaction and product quality. This study focuses oncharacterizing and predicting reviews on e-commerce websites using advanced natural language processing(NLP) techniques. By analyzing a dataset of reviews, we explore various factors that contribute to positiveand negative sentiments, such as product features, service quality, and user experience. Leveraging machine learning algorithms, we develop predictive models to anticipate the sentiment of new reviews, of eringbusinesses a proactive approach to managing customer feedback and improving overall performance. In the realm of e-commerce, customer reviews wield significant influence over consumer behavior and brand reputation. This study delves into the characterization and prediction of reviews on e-commerce platforms, employing advanced natural language processing (NLP) techniques and machine learning models. Our research centers on deciphering the multifaceted dynamics that shape review sentiments, encompassing aspects such as product attributes, customer service interactions, and overall user satisfaction. Through comprehensive analysis of a diverse review dataset, we identify key factors driving positive and negativesentiments. Subsequently, leveraging state-of-the-art NLP methodologies and predictive modeling, we construct robust frameworks for anticipating the sentiment of forthcoming reviews. This predictive capability mpowers businesses to proactively manage customer perceptions, optimize product of erings, and elevateservice standards, thereby fostering sustained growth and competitive advantage in the digital

CHARACTERIZING AND PREDICTING REVIEWS ON E-COMMERCE WEBSITE

"CHARACTERIZING AND PREDICTING REVIEWS ON E-COMMERCE WEBSITE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.109-113, June-2024, Available :http://www.jetir.org/papers/JETIRGL06020.pdf

"CHARACTERIZING AND PREDICTING REVIEWS ON E-COMMERCE WEBSITE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp109-113, June-2024, Available at : http://www.jetir.org/papers/JETIRGL06020.pdf