The multi-label emotion classification task aims to identify all possible emotions in a written
text that best represent the author's mental state. In recent years, multi-label emotion …

Lexicon-based sentiment and emotion analysis methods are widely used particularly in
applied Natural Language Processing (NLP) projects in fields such as computational social …

We introduce EmotionArcs, a dataset comprising emotional arcs from over 9,000 English
novels, assembled to understand the dynamics of emotions represented in text and how …

Multimodal speech emotion recognition (SER) and sentiment analysis (SA) are important
techniques for human-computer interaction. Most existing multimodal approaches utilize …

Emotion detection in text is a fundamental aspect of affective computing and is closely linked
to natural language processing. Its applications span various domains, from interactive …

Abstract Facebook, Twitter, Instagram, and other social media sites allow anonymity and
independence. People exert their right to free expression without fear of repercussions …

In this paper, we hypothesize that sarcasm detection is closely associated with the emotion
present in memes. Thereafter, we propose a deep multitask model to perform these two …

This paper presents a scheme for emotion annotation and its manual application on a genre-
diverse corpus of texts written in French. The methodology introduced here emphasizes the …

This paper examines the role of emotion annotations to characterize extremist content
released on social platforms. The analysis of extremist content is important to identify user …

This study created a visualized folksonomy classification that integrates topic icons and
emojis to help children to find books that they like in library settings. The National Library of …