Emotional Analysis of Public Opinions in Colleges and Universities:Based on Naive Bayesian Classification Method

Abstract

In this paper, we use the emotion dictionary to process and express the public opinion texts of colleges and universities. We construct the public opinion texts of colleges and universities sentiment emotional classifier based on Naive Bayesian theory, and then judge the emotional tendency of public opinion texts of colleges and universities. Experiments show that the method has the characteristics of fast classification and high accuracy, and is suitable for the public opinion system of colleges and universities. The method facilitates the university management's interpretation and mastery of the public opinions related to the school in the network, promotes and guides the positive energy in the communication network, corrects the vulgar and biased content, prevents the forwarding and dissemination of inappropriate speech, and establishes a positive campus environment among the teachers and students of the whole school.