Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …

The omnipresence of numerous information sources in our daily life brings up new
alternatives for emotion recognition in several domains including e-health, e-learning …

Abstract Emotion Recognition in Conversations (ERC) is crucial in developing sympathetic
human-machine interaction. In conversational videos, emotion can be present in multiple …

The modeling of conversational context plays a vital role in emotion recognition from
conversation (ERC). In this paper, we put forward a novel idea of encoding the utterances …

Sentiment analysis in conversations has gained increasing attention in recent years for the
growing amount of applications it can serve, eg, sentiment analysis, recommender systems …

When available, multimodal data is key for enhanced emotion recognition in conversation.
Text, audio, and video in dialogues can facilitate and complement each other in analyzing …

Emotion detection in dialogues is challenging as it often requires the identification of
thematic topics underlying a conversation, the relevant commonsense knowledge, and the …

This report presents a study on the emotional dialogue capability of ChatGPT, an advanced
language model developed by OpenAI. The study evaluates the performance of ChatGPT on …

The surge in internet use to express personal thoughts and beliefs makes it increasingly
feasible for the social NLP research community to find and validate associations between …

Emotion recognition in conversation (ERC) has received increasing attention from the
research community. However, the ERC task is challenging, largely due to the complex and …