International Journal of Scientific Research and Engineering Development

This study investigates the use of sentiment analysis and sentiment mining for extracting meaningful information from user-generated content (UGC) posted on social media, reviews of products or services via e-commerce sites such as Amazon, and posts on various digital forums. The goal of this research is to identify trends in public opinion, classify sentiments as positive/negative/neutral, and assess the effect of those sentiments on the decision-making processes made by companies and governments. The methodology for this research project involves using machine learning and natural language processing (NLP) to carry out sentiment analysis using datasets obtained from various social networking sites such as Twitter and review sites like Amazon. The research will employ several methods ranging from preprocessing text data, extracting features, and classification methods (e.g., Naive Bayes (NB), Support Vector Machine (SVM), deep learning), and multiple other machine-learning algorithms to accomplish its objectives. The anticipated results of this research include a prototype system for performing sentiment analysis, improved classification accuracy when performing sentiment classifications, and greater potential for Indian small and medium enterprises (SMEs) as well as Indian policymakers to adopt the research outputs.

Kushal Gajera, Santosh Sonone,"Sentiment Analysis and Opinion Mining" International Journal of Scientific Research and Engineering Development, V9(3): Page(255-261) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.