Perception Assessment of Indian Colleges through Twitter Data

Abstract

Technology has changed the traditional methods of quality check and analysis. Customer reviews are serving as the most important and decisive parameters in deciding the quality and effectiveness of any service, brand or product. Social media sites like Twitter have become an open and goto platform where millions of users tend to express their opinions freely about technologies and brands. While we know that Twitter data is extremely informative but analysis and concluding decisive results out of it is very challenging. The primary reason is its disorganized and humongous nature. It requires very efficient methods and techniques to extract such large data and perform operations so that meaningful results can be obtained. This project is an effort to computationally identify and categorize opinions expressed in a set of tweets, aiming to determine the sentiment of the students, teachers and other organisation in the field of education towards top colleges in India. The categorical results are broadly divided into three sentiments namely positive, negative and neutral. The process involves various pre-processing steps to generate the tokens and then implementing algorithms to derive the sentiments involved in those tweets.