情绪检测
计算机科学
领域(数学)
感觉
情绪识别
情绪分类
数据科学
面部表情
社会化媒体
情感计算
深度学习
人工智能
心理学
万维网
社会心理学
数学
纯数学
作者
Abdullah Al Maruf,Fahima Khanam,Md. Mahmudul Haque,Zakaria Masud Jiyad,M. F. Mridha,Zeyar Aung
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-1
被引量:1
标识
DOI:10.1109/access.2024.3356357
摘要
Emotion detection has become an intriguing issue for researchers because of its psychological, social, and commercial significance. People express their feelings directly or indirectly through facial expressions, language, writing, or behavior. An emotion detection tool is a critical and practical way of recognizing and categorizing moods with various applications. Artificial intelligence is often used in research to identify emotions. Machine learning and deep learning algorithms produce high-quality solutions for diagnosing emotional diseases in social media users. Numerous studies and survey articles have been published on emotion detection based on textual data. However, most of these studies did not comprehensively address emerging architectures and performance analysis in emotion detection. This paper provides an extensive survey of state-of-the-art systems, techniques, and datasets for textual emotion recognition. Another goal of this study is to emphasize the limitations and provide up-and-coming research directions to fill these gaps in this rapidly evolving field. This survey paper investigated the concepts and the performances of different categories of textual emotion detection models, approaches, and methodologies.
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