Understanding Sentiment Words and Truthful Opinions from Academic Feedbacks


Sonai Muthu Anbananthen, Kalaiarasi and Kannan, Rajkumar (2013) Understanding Sentiment Words and Truthful Opinions from Academic Feedbacks. Australian Journal of Basic and Applied Sciences, 7 (6). pp. 299-306. ISSN 1991-8178

[img] Text
Restricted to Repository staff only

Download (266kB)


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.

Item Type: Article
Uncontrolled Keywords: Text Analytics, Sentiment Classification, Academic feedbacks, Opinion Mining, Quality metrics
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 13 Jan 2017 05:01
Last Modified: 13 Jan 2017 05:01
URII: http://shdl.mmu.edu.my/id/eprint/6120


Downloads per month over past year

View ItemEdit (login required)