State-of-the-Art Methods for Fine-Grained Emotion Detection from Malayalam Text using Deep Learning: A Survey
K Anuja, P. C. Reghu Raj, Remesh Babu K R · 2022
Social media has changed the way people express their opinions, views, and feedback about anything in their minds. This large volume of sentiment-rich data needs to be examined properly in order to comprehend the mood, attitude, or sentiment underlying those words. Computers can process, interpret, and analyze vast volumes of natural data using natural language processing (NLP), which helps them to comprehend human languages. Now all organizations are looking for more fine-grained sentiment analysis to plan their business strategy. This paper investigates state-of-the-art textual data analysis using NLP techniques. The increased use of Indian languages in communicating platforms is a challenging task for opinion mining. In this paper, we survey the state-of-the-art methods based on deep learning and fuzzy rules for sentiment analysis.