https://scraptical-main.vercel.app/
TARP Project
Our project is focused on developing a cutting-edge web scraping application capable of extracting and analyzing sentiment data from vast volumes of product reviews on Amazon. Our goal is to categorize each review as positive, negative, or neutral, using sophisticated algorithms that take into account various factors such as language used, length of the review, and frequency of certain keywords.
Our application employs advanced natural language processing (NLP) techniques to extract and analyze sentiment data, allowing us to gain a deep understanding of how customers perceive a particular product. We aim to provide businesses with valuable insights into how their products are perceived in the market, which can help them identify areas for improvement and enhance customer satisfaction.
Our algorithms assign a weight to each review based on its perceived impact, with the aim of providing a comprehensive view of customer sentiment. Our approach enables us to provide a nuanced understanding of how customers feel about a particular product, taking into account both positive and negative aspects of the product.
Our project has enormous potential to benefit businesses in a variety of industries, enabling them to gain valuable insights into customer sentiment, which can be used to improve their products and enhance customer satisfaction. By leveraging advanced NLP techniques and sophisticated algorithms, we are paving the way for a more insightful and data-driven approach to customer analysis.