Lexicon Based Sentiment Analysis of Open-Ended Students’ Feedback
Khin Zezawar Aung1, Nyein Nyein Myo2
1Khin Zezawar Aung, Faculty of Information Science, University of Computer Studies, Mandalay, Myanmar.
2Nyein Nyein Myo, Faculty of Information Science, University of Computer Studies, Mandalay, Myanmar.
Manuscript received on 18 December 2018 | Revised Manuscript received on 27 December 2018 | Manuscript published on 30 December 2018 | PP: 46-51 | Volume-8 Issue-2, December 2018 | Retrieval Number: B5530128218/18©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Sentiment analysis is helpful in finding the opinion of writer’s feeling towards a specific topic. Teaching evaluation is a useful tool of assessment for teaching and courses at many universities, colleges and schools. Mostly close-ended questions and open- ended questions are used in teaching evaluation process. This paper used open-ended questions to provide the opinion result for teachers’ effectiveness of teaching and over all course condition. In this paper, teaching sentiment lexicon, Afinn lexicon and Opinion lexicon are used to get the scores of opinion words in feedback comments. The students’ feedback comments are analyzed by using three methods and display the opinion result as positive, negative and neutral class. According to the experimental results, the intensifier words are needed to consider in some feedbacks to get the correct opinion result. The accuracy of Method 1 using teaching sentiment lexicon is better than other two methods.
Keywords: Lexicon Based, Opinion Mining, Sentiment Analysis, Students’ Feedback.
Scope of the Article: Data Mining