Sentiment Analysis: Aspect-based analysis for Market Insights and Customer Feedback Valuation

E-commerce platforms have been witnessing a rapid expansion leading to an overwhelming amount of customer reviews which can be a source to obtain valuable insights on performance of the product and customer satisfaction. This paper delves on a machine learning approach to perform sentimental analysis on customer reviews. With a major focus on aspect based sentimental analysis(ABSA) for customer feedback valuation on various headset brands. With flipkart reviews dataset, the experiment aims to develop a model that can classify the overall sentiment of the consumer into positive or negative and dives deeper into product aspects such as sound quality, battery life, and comfort. This involves data preprocessing, sentimental scoring, aspect extraction and model evaluation using BERT. This will help us have strong framework for identifying actionable insights, allowing businesses to enhance marketing strategies and improve customer service. In the future the project can be developed further to include multilingual datasets and refining the accuracy of the model, examining its application to various social media platform