Students’ input in terms of feedback is critical for any educational establishment to assess the performance of the faculty. Most of the methods will take care of the subjective assessments of students productively while feedbacks on the quality are left unattended. This paper proposes a supervised perspective to put together the opinion mining framework based on Gated RNN model. The layer that forms the primary is intended to predict the aspects that are described inside and the later depicts the corresponding direction i.e. whether it is positive / negative or Impartial on the aspects that are anticipated. Unlike the other methods that are available in the literature and which use RNN techniques, the proposed method follows basic engineering and hence is less multifaceted in nature. The data for the research was collected in real time from the final year under graduate computer science students from Karpagam Academy of Higher Education. The framework accomplishes a decent precision utilizing the area-installing-layer in the two errands: aspect extraction and sentiment orientation. Based on the extensive study of the literature, our method is a novel technique which evaluates the performance based on sentiment analysis with the feedback obtained from students.
Volume 12 | 01-Special Issue