Abstract: “Opinions are essential for developing the services and facilities within the education domain. Students tend to express their opinions positively and negatively in the social network platform, such as Twitter and Facebook, toward various education universities. Collecting and analyzing those opinions will improve the overall education quality within the university’s campus. In this paper, results are presented for the collected and analyzed tweets using Bag of Words (BoW) and Word Sense Disambiguation (WSD) approaches. The results include, tweets distribution for the chosen Malaysian universities, opinion mining timeline to illustrate the student responsiveness against the timeline, and polarity classification for the university entities and objects. The figure results are produced using nodebox and matplot libraries for python.”

Keywords: opinion mining, data mining, polarity classification, bag of words, word sense disambiguation