Aspect Term Extraction and Categorization for Chinese MOOC Reviews

Sentiment analysis has become one of the most active topics in education research. So far, however, there has been little discussion about the recent application of sentiment analysis for Chinese MOOC reviews. Therefore, this paper sheds light on some fine-grained sentiment analysis technology to benefit the current students and education practitioners. Firstly, we focus on extracting aspect terms associated with the course via dependency parsing and sentiment word lexicons. Secondly, we categorize the aspect terms with the Naive Bayes. Experimental results effectively demonstrate that the proposed approach and refine the granularity of sentiment categories in higher education. This paper makes sentiment analysis possible to increase students’ learning retention and improve teachers’ performance in online teaching.