Transformer-based Text Classification on Unified Bangla Multi-class Emotion Corpus

While enough research has been done to identify emotions from visual and auditory data, emotion recognition from textual data is still a new and active study topic [4]. WeChat, Twitter, YouTube, Instagram, and Facebook, as well as other Web 2.0 platforms or social networks (SNs), have recently emerged as the most important platforms for social communication [32], education [23], information exchange [31], and other purposes [2, 9, 10] among a variety of people. Users of SN connect, share their thoughts, feelings, and ideas, and participate in discussion groups. Text conversation, or more specifically, emotion classification (EC), is essential to comprehending people's activities since the internet's invisible nature has made it possible for a single user to engage in violent SN speech data [19]. EC is a subset of sentiment analysis (SA).