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Tracking Student Sentiment from Social Media

Dahai Guo
Department of Software Engineering, Florida Gulf Coast University, Fort Myers, FL, USA
Abstract—This paper describes a framework that utilizes technologies to track students’ sentiment using their input to social media. Social media has accumulated a vast amount of textual inputs from students. That amount is still growing rapidly. While it is desirable to gain insights from these inputs, it is impossible to manually analyze individual inputs. Fortunately, computer technologies exist for summarizing textual data. One of such technologies is referred to as sentiment analysis, which has been used in the business world for tracking customers’ opinions on certain products or services. The framework, introduced in this paper uses these sentiment analysis technologies to track students’ sentiment. It consists of three components: 1) data collector, 2) sentiment analyzer, and 3) result reporter. In addition, this paper also presents a case study where students’ comments on ratemyprofessors.com are analyzed.

Index Terms—sentiment analysis, information retrieval, social media

Cite: Dahai Guo, "Tracking Student Sentiment from Social Media," Vol. 6, No. 2, pp. 80-83, May, 2015. doi:10.12720/jait.6.2.80-83
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