Product Recommendation using Sentimental Analysis

Abstract— This paper aims to employ Natural Language Processing to carry out real-time sentiment analysis with high accuracy. Sentiment analysis involves identifying the positive, negative, or neutral tone of text data through systematic extraction, quantification, and analysis of affective states and subjective information, using text analysis and natural language processing. Sentiment analysis is widely used in various fields, such as marketing, customer service, clinical medicine, and others, to analyze comments, survey results, online and social media content, and healthcare materials. The primary objective of this study is to perform sentiment analysis on service-based feedback. By analyzing customer reviews, it is possible to quickly determine whether they are satisfied, dissatisfied, or neutral, and to gain insights into the specific reasons behind their opinions about a product. This information can then be utilized to recommend products that have received positive feedback from customers.