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Student reviews and comments on RateMyProfessor.com reflect realisticlearning experiences of students. Such information provides a large-scale datasource to examine the teaching quality of the lecturers. In this paper, wepropose an in-depth analysis of these comments. First, we partition our datainto different comparison groups. Next, we perform exploratory data analysis todelve into the data. Furthermore, we employ Latent Dirichlet Allocation andsentiment analysis to extract topics and understand the sentiments associatedwith the comments. We uncover interesting insights about the characteristics ofboth college students and professors. Our study proves that student reviews andcomments contain crucial information and can serve as essential references forenrollment in courses and universities.

Are Top School Students More Critical of Their Professors? Mining Comments on RateMyProfessor.com