Paper Title
An Artificial Neural Network based Teacher Learning Model for Sentiment Classification

Abstract
The social media platform has given the great opportunity to the industries to obtain feedback of services or products provided by them. This huge amount of data available on social media platforms are playing a key role to understand the requirements and opinions of the users. Here we brought together the Teacher Learning Model with an Artificial Neural Network approach to detect the sentiment class of the social media content. In this study, it is observed that the use of an Artificial Neural Network for the learning of feature set in binary format, enhances the efficiency evaluation parameters of the Teacher Learning Model for sentiment class detection. Keywords - Text Mining, Sentiment, ANN, Precision, Recall, Accuracy, F-Measure, TNR, FNR, and FPR