Social networking platforms have become an essential means for communicating feelings to
the entire world due to rapid expansion in the Internet era. Several people use textual …

In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …

Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …

Sentiment analysis has been a hot research topic in natural language processing and data
mining fields in the last decade. Recently, deep neural network (DNN) models are being …

Astoundingly, recent technological advancements have enabled robots to display emotions.
Yet, while emotional expression is valued in the field of service, understanding emotions in …

Emotion detection (ED) is a branch of sentiment analysis that deals with the extraction and
analysis of emotions. The evolution of Web 2.0 has put text mining and analysis at the …

Emotion is intrinsic to humans and consequently, emotion understanding is a key part of
human-like artificial intelligence (AI). Emotion recognition in conversation (ERC) is …

Messages in human conversations inherently convey emotions. The task of detecting
emotions in textual conversations leads to a wide range of applications such as opinion …

In this paper, we present the SemEval-2019 Task 3-EmoContext: Contextual Emotion
Detection in Text. Lack of facial expressions and voice modulations make detecting …

Capturing complex contextual dependencies plays a vital role in Emotion Recognition in
Conversations (ERC). Previous studies have predominantly focused on speaker-aware …