Sentiment Analysis of Educational Institutions for Getting Admission

The “Sentiment Analysis of Educational Institutions for Admissions” project introduces a dynamic web application that leverages sentiment analysis techniques to provide valuable insights into the sentiment associated with reviews of various educational institutions. Sentiment analysis, a subset of Natural Language Processing (NLP), is employed to gauge the sentiment expressed in text, categorizing it as positive, negative, or neutral. The project aims to facilitate decision-making for potential admissions by offering a comprehensive view of sentiment trends. The web application utilizes the VADER (Valence Aware Dictionary and sentiment Reasoner) sentiment analysis tool to analyze reviews of educational institutions. Upon uploading review datasets, the application processes and visualizes the sentiment distribution, providing users with an overview of the sentiment patterns within different institutions. The system’s interface allows users to select specific educational institutions for sentiment analysis, presenting a percentage breakdown of positive, negative, and neutral sentiments in the reviews. Furthermore, the project introduces a ranking mechanism that ranks educational institutions based on their sentiment scores and reviews. This feature offers users a streamlined method to compare institutions and make informed decisions regarding potential admissions. To enhance the presentation of sentiment analysis results, the project employs the Matplotlib library to generate pie charts illustrating sentiment distribution and admission likelihood percentages. The project’s web application not only showcases the application of sentiment analysis in real-world scenarios but also serves as a practical tool for students, parents, and educational institutions. By incorporating sentiment analysis into the admissions process, the project offers a fresh perspective on evaluating educational institutions’ reputation and quality through the lens of sentiment expres