@Article{cmc.2020.07920,
AUTHOR = {Yun Wang, Fazli Subhan, Shahaboddin Shamshirband, Muhammad Zubair Asghar, Ikram Ullah, Ammara Habib},
TITLE = {Fuzzy-Based Sentiment Analysis System for Analyzing Student Feedback and Satisfaction},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {2},
PAGES = {631--655},
URL = {http://www.techscience.com/cmc/v62n2/38268},
ISSN = {1546-2226},
ABSTRACT = {The feedback collection and analysis has remained an important subject matter 
for long. The traditional techniques for student feedback analysis are based on 
questionnaire-based data collection and analysis. However, the student expresses their 
feedback opinions on online social media sites, which need to be analyzed. This study 
aims at the development of fuzzy-based sentiment analysis system for analyzing student 
feedback and satisfaction by assigning proper sentiment score to opinion words and 
polarity shifters present in the input reviews. Our technique computes the sentiment score 
of student feedback reviews and then applies a fuzzy-logic module to analyze and 
quantify student’s satisfaction at the fine-grained level. The experimental results reveal 
that the proposed work has outperformed the baseline studies as well as state-of-the-art 
machine learning classifiers.},
DOI = {10.32604/cmc.2020.07920}
}