Sentiments or opinions from social media provide the most up-to-date and inclusive
information, due to the proliferation of social media and the low barrier for posting the …

Affective computing is an emerging interdisciplinary research field bringing together
researchers and practitioners from various fields, ranging from artificial intelligence, natural …

In this paper, we address the task of utterance level emotion recognition in conversations
using commonsense knowledge. We propose COSMIC, a new framework that incorporates …

Emotion detection in conversations is a necessary step for a number of applications,
including opinion mining over chat history, social media threads, debates, argumentation …

Multimodal sentiment analysis is a developing area of research, which involves the
identification of sentiments in videos. Current research considers utterances as independent …

Emotion recognition in conversations is crucial for building empathetic machines. Present
works in this domain do not explicitly consider the inter-personal influences that thrive in the …

Emotions are an inherent part of human interactions, and consequently, it is imperative to
develop AI systems that understand and recognize human emotions. During a conversation …

Emotion recognition in conversations is crucial for the development of empathetic machines.
Present methods mostly ignore the role of inter-speaker dependency relations while …

Technology has enabled anyone with an Internet connection to easily create and share their
ideas, opinions and content with millions of other people around the world. Much of the …

Dialogue emotion detection is always challenging due to human subjectivity and the
randomness of dialogue content. In a conversation, the emotion of each person often …