Open AccessBilingual Lexicon Approach to English-Filipino Sentiment Analysis of Teaching Performance
Author(s) -
Caren Ambat Pacol,
Thelma D. Palaoag
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1077/1/012044
Subject(s) - sentiment analysis , complement (music) , computer science , lexicon , artificial intelligence , natural language processing , machine learning , biochemistry , chemistry , complementation , gene , phenotype
The aim of this study is to formulate a strategy that can possibly calculate teacher performance by analyzing textual feedback. Expressing textual responses in quantitative form like average sentiment rating can actually provide opportunities for administrators to see if the numerical ratings given complement that of the comments. Our approach was designed to enable processing bilingual textual data. Findings of this study shows that there is strong correlation between teaching performance actual mean rating and average sentiment rating. Furthermore, the approach employed obtained 86% accuracy indicating that it is an encouraging technique, capable of analyzing the students' textual responses. In future work, the use of POS tagging can be explored to improve sentiment analysis accuracy. Employing machine learning methods may also be considered to discover techniques and alternative approaches to sentiment classification.