Effects of sentiment discreteness on MOOCs' disconfirmation: text analytics in online reviews

In Massive Open Online Courses (MOOCs), online reviews serve as a basis for teachers to improve their courses. The disconfirmation effect of online reviews, i.e. the inconsistency between the level of attention paid to a course factor and the actual weight of that factor's influence on learner satisfaction, leads to erroneous judgments by teachers. Based on the two-factor theory of emotion, 4,070 courses and 165,705 online reviews are adopted as a corpus to identify the effect of learner sentiment on the disconfirmation effect. The empirical results show that there is a significant disconfirmation effect for negative reviews, but not for positive ones. A fine-grained analysis on negative sentiment finds that reviews containing more sadness and anger sentiments have a stronger disconfirmation effect. A comparison of course types reveals that the disconfirmation effect is stronger for instrument-based courses than that for knowledge-based and practice-based ones. In addition, negative word-of-mouth weakens the disconfirmation effect of sadness and anger reviews and enhances the disconfirmation effect of positive reviews. Further, learner's reputation weakens the disconfirmation effect of sadness reviews and enhances the disconfirmation effect of positive and anger reviews.