Emotion Detection From Text

Abstract

Detecting emotion from text is a relatively new classification task and advancements in textual analysis have allowed the area of emotion detection to become a recent interest in the field of natural language processing. There is still a question on how to detect emotion from a text input. To solve this problem, this project generates an Emotion Detection Model to extract emotion from text at the sentence level. The proposed methodology does not depend on any existing affect lexicons such as WordNet Affect. Our method detects emotion from a text-input by searching direct emotional key words from that input. To make the detection more accurate, emotion-affect-bearing words and phrases were also analyzed. The experiments show that the method could generate a good result for emotion detection from text input. To detect emotion from text we have considered Ekman‟s six emotions class (joy, sadness, anger, disgust, fear, surprise). Our approach showed above 77% accuracy in detecting emotion from text input. Keyword:Language Processing, EmotionEstimation, Methodologies, Experiment, Result &Discussion, Futer Network.