Faculty rating system based on student feedbacks using sentimental analysis

Educational Data Mining is a prominent area to explore information in educational fields using data mining algorithms. In this paper we have used few learning algorithms to effectively rate the faculty belonging to an educational institute on the basis of feedback submitted by the students. Our proposed model uses sentimental analysis and machine learning classifier algorithms for capturing the emotions from the students feedback system. This model gives an accurate and efficient way to rate the faculty belonging to a particular educational institute. With this proposed model the faculty will be evaluated and rated with certain specified parameters which will help us to improve the academic and education standard.