Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to
sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing …

Sarcasm identification on text documents is one of the most challenging tasks in natural
language processing (NLP), has become an essential research direction, due to its …

Sarcasm is often expressed through several verbal and non-verbal cues, eg, a change of
tone, overemphasis in a word, a drawn-out syllable, or a straight looking face. Most of the …

This paper presents the first shared task on irony detection: given a tweet, automatic natural
language processing systems should determine whether the tweet is ironic (Task A) and …

Sarcasm is a type of nonliteral language, where people may express their negative
sentiments with the use of words with positive literal meaning, and, conversely, negative …

Pragmatics, situated in the domains of linguistics and computational linguistics, explores the
influence of context on language interpretation, extending beyond the literal meaning of …

Sarcasm detection is a challenging natural language processing task for sentiment analysis.
Existing deep learning based sarcasm detection models have not fully considered sentiment …

Sarcasm detection is the task of identifying irony containing utterances in sentiment-bearing
text. However, the figurative and creative nature of sarcasm poses a great challenge for …

We recorded and preprocessed ZuCo 2.0, a new dataset of simultaneous eye-tracking and
electroencephalography during natural reading and during annotation. This corpus contains …

Computational models for sarcasm detection have often relied on the content of utterances
in isolation. However, the speaker's sarcastic intent is not always apparent without additional …