Automatic Sentiment Classification of tweets using Natural Language Processing

Analyzing the Opinions of Twitter Users about Railway Services

Abstract

Text-based communication such as an email tweet and our statuses on a daily basis become one of the most common forms of expression. As a result, lot of unstructured data is generated. So analyze large quantities of text data is now a key way to understand what people is thinking. Sentiment Analysis is the keen area of research which concentrates on analyzing the opinions of users about any topic and classifies them into positive or negative reviews. Text like tweets on twitter helps us find trending topics in the world. Sentiment analysis is one of the important task of natural language processing Natural language processing techniques are used to analyze text, providing a way for computers to understand human language. Data is collected from twitter on railway services reviews. NLTK is used for building Python programs to work with human language data. Different machine learning approaches are used to build the classification model for training and testing the data. The performance of these models are evaluated and compared by using accuracy metric.