Review of Databases used for Text Based Emotion Detection
Shrikala Deshmukh · 2024
Currently most all the information sharing takes place in the form of Text-based input. Diverse information sources, encompassing speech, text, and visual elements, offer opportunities for analyzing emotions. Presently, written content manifests in various formats like micro-blogs, news articles and social media posts. This content proves to be an asset for the practice of text mining, enabling the exploration and revelation of multifaceted aspects, including emotions. People share their emotions about a topic or any subject through text. Emotion recognition falls within the realm of sentiment analysis, focusing on the identification and examination of emotions. This paper is a review of advancements in Text-based emotion detection and state-of-the-art techniques and methodologies employed in text-based emotion recognition previously used deep learning, and the machine learning approach.