Understanding Sentiment Words and Truthful Opinions from Academic Feedbacks
Kalaiarasi Sonai, Muthu Anbananthen, Rajkumar Kannan · Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University) · 2013
Online feedbacks have become increasingly popular means of gathering students’ reviews and judging the quality of various services offered by an institution, such as courses, teaching, evaluation, infrastructure and many others. Generally, academic feedbacks include values through numerical ratings and free text comments. In this paper, we employ a natural language-based approach to extract features of feedbacks, capture sentiment words from those feedbacks and build opinion vocabulary from the corpus of academic feedbacks. Also, we focus on studying student behaviour while reporting their feedbacks. Particularly, we investigate the reliability of quantitative features through numerical ratings that students offer, by estimating the linguistic evidence from the free text in the feedback.