NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment
analysis and related tasks, researchers have therefore used binarized emoticons and …

Abstract Big Data and Deep Learning algorithms combined with enormous computing power
have paved ways for significant technological advancements. Technology is evolving to …

We can often detect from a person's utterances whether he or she is in favor of or against a
given target entity—one's stance toward the target. However, a person may express the …

Sentiment analysis is the task of automatically determining from text the attitude, emotion, or
some other affectual state of the author. This chapter summarizes the diverse landscape of …

Emotion detection has become an intriguing issue for researchers owing to its
psychological, social, and commercial significance. People express their feelings directly or …

This paper examines the task of detecting intensity of emotion from text. We create the first
datasets of tweets annotated for anger, fear, joy, and sadness intensities. We use a …

Image tagging is an essential step for developing Automatic Image Annotation (AIA)
methods that are based on the learning by example paradigm. However, manual image …

Recent advances in machine learning have led to computer systems that are humanlike in
behavior. Sentiment analysis, the automatic determination of emotions in text, is allowing us …

Emotions are physiological states generated in humans in reaction to internal or external
events. They are complex and studied across numerous fields including computer science …

Purpose The purpose of this paper is to study sarcasm in online text–specifically on twitter–
to better understand customer opinions about social issues, products, services, etc. This can …