Sentiment analysis from text consists of extracting information about opinions, sentiments,
and even emotions conveyed by writers towards topics of interest. It is often equated to …

Social media is used to categorise products or services, but analysing vast comments is time-
consuming. Researchers use sentiment analysis via natural language processing …

Detecting emotions in microblogs and social media posts has applications for industry,
health, and security. Statistical, supervised automatic methods for emotion detection rely on …

In this paper, we show how sentiment analysis can be used in tandem with effective
visualizations to quantify and track emotions in mail and books. We study a number of …

Emotions are a crucial part of compelling narratives: literature tells us about people with
goals, desires, passions, and intentions. Emotion analysis is part of the broader and larger …

Detecting emotions in microblogs and social media posts has applications for industry,
health, and security. However, there exists no microblog corpus with instances labeled for …

In this work we present a new dataset of literary events—events that are depicted as taking
place within the imagined space of a novel. While previous work has focused on event …

Understanding word-level emotion in terms of both category and intensity has always been
considered an essential step in addressing text emotion classification tasks. Existing studies …

As technology and human-computer interaction advances, there is an increased interest in
affective computing. One of the current challenges in computational speech and text …

Emotion dynamics is a framework for measuring how an individual's emotions change over
time. It is a powerful tool for understanding how we behave and interact with the world. In …