Survey: Emotion Recognition from Text Using Different Approaches

Abstract

Text Processing is a method for comprehending, analyzing, and cleaning text as well as performing actions on the same data. The technique is used to extract meaningful data from text. It is a written form of communication to express emotions through text. Happy, neutral, fear, sadness, surprise, disgust, and anger are the most common emotional expressions. As a result, in the social media era, identifying emotions from text is especially important. A survey of operational methods and approaches for identifying emotion from textual data is discussed in this paper. This research primarily focuses on existing datasets and methodologies that incorporate a Lexical keyword, Machine Learning and Hybrid-based approach.