Open AccessSentiment Evaluation of Public Transport in Social Media using Naïve Bayes Method
Author(s) -
Nur Khaleeda Othman,
Masnida Hussin,
Rosli Mahmood
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a2636.109119
Subject(s) - reputation , social media , scope (computer science) , naive bayes classifier , computer science , sentiment analysis , bayes' theorem , work (physics) , artificial intelligence , world wide web , bayesian probability , engineering , sociology , support vector machine , mechanical engineering , social science , programming language
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.