Emotion recognition in text is an important natural language processing (NLP) task whose
solution can benefit several applications in different fields, including data mining, e-learning …

Social media is a widespread platform that provides a massive amount of user-generated
content that can be mined to reveal the emotions of social media users. This has many …

Affective tasks, including sentiment analysis, emotion classification, and sarcasm detection
have drawn a lot of attention in recent years due to a broad range of useful applications in …

Emotions are highly useful to model human behavior being at the core of what makes us
human. Today, people abundantly express and share emotions through social media …

Confusion, fear and mixed sentiments prevail in the minds of people towards what is
arguably one of the most important of dynamics of modern human society: Artificial …

Emotions are highly useful in modeling human behavior being at the core of what makes us
human. Research in Affective Computing deals with developing computational systems …

The dream of enabling machines to think like humans has emerged ever since the invention
of computers. Over the years people have tried to build machine-based systems that can …

The role of detecting affects from text is to detect affective states such as mood, sentiment
and emotions from textual data. The main affective tasks, including sentiment analysis …