Summary and Outlook

In this chapter, we will discuss the challenges (i.e., emotion description, data imbalance, language imbalance, domain relevance, understanding short texts, implicit emotion analysis, and DL model training) and future research trends (i.e., multi-language emotion classification, multi-modal emotion classification, cross-domain emotion classification, emotion classification based on social network analysis, emotion classification based on big data analysis, automatic recognition of negative emotions in text, evolution analysis negative emotion, emotion cause extraction, and optimizing large language model) in TEC. This trend has drawn an increasing number of researchers away from traditional machine learning to DL for their scientific research.