Paper Title
DEEP LEARNING BASED TEXT CLASSIFICATION MODEL FOR EMOTION DETECTION

Abstract
Emotion detection is a method to detect the specific emotions rather than just classifying as positive or negative. Recently, several research works have been evolved on emotion recognition which mainly focuses on facial expressions or gestures. But emotion detection from text data is really a difficult task, as it does not contain any explicit signs of expressions. Keyword and lexicon-based techniques have certain drawbacks, as they are based on semantic relations. Hence machine learning (ML) based techniques are effective in classifying the emotions from the text. This paper designs a Deep Learning (DL) based text classification model for emotion detection. The proposed model can predict the emotion of any input texts. The proposed model is implemented in Python 3.0 with Keras module. Experimental results prove that the DL model achieves increased precision, recall and F1 score values. Keywords - Emotion detection, Text classification, Deep learning, Convolution Neural networks