Deep Learning Approach for Emotion Recognition Analysis in Text Streams

1. Introduction

Emotion recognition (El Hammoumi et al, 2018) is the process of identifying human emotion. Generally, people differ in their precision at the recognition of the feelings of others. The use of technology to assist people with emotion detection (Yoon et al, 2019) is a relatively growing area. Currently, most research has been performed on automating the recognition of facial expression from the video (Manogaran et al, 2019), spoken word from audio (Ahmad et al, 2021), written expression from text and physiology expressions from wearable devices (Mukhopadhyay et al, 2020). Emotion identification (Alazab,2020) from text is a recent essential research area in the field of natural language processing (NLP) and deep learning (Mamoun Alazab et al, 2019), which may reveal some valuable input for a variety of purposes. Nowadays, a large volume of textual data has been produced in real-time due to communication technologies' development (Iqbal et al, 2019). Some of the applications are social media posts, micro-blogs, news articles, online teaching and assessment, customer reviews, etc. (Kwon et al, 2016).