Sentiment evaluation of public transport in social media using naïve bayes method

Abstract

Nowadays, there is a trend in business organization to use social media as a medium to get feedback from customers. This gives advantage in improving the business values such as increasing customers’ satisfactions and building better company reputation. However, the response and feedback from the customers are varies and hold different perspectives. It might be led to ambiguous answer.In this work, we utilized Naïve Bayes machine learning approach for analyzing sentiment at social media on transportation services. We collected all feedback from Facebook and Twitter about transportation services. From the unstructured comments and feedback, we classified accordingly to determine the related scope of the sentiment. By using the Naïve Bayes method those massivecomments and feedback are presented in appropriate way and easier to understand.