Sentiment Evaluation of Public Transport in Social Media using Naïve Bayes Method
Nur Khaleeda Othman1, Masnida Hussin2, Raja Azlina Raja Mahmood3
1Nur Khaleeda Othman, Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, Serdang.
2Masnida Hussin, Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, Serdang.
3Raja Azlina Raja Mahmood, Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, Serdang.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2305-2308 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2636109119/2019©BEIESP | DOI: 10.35940/ijeat.A2636.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: Naïve Bayes machine learning, sentiment analysis, social networking, and transportation service.