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 …

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 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 …

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 …

Eye‐tracking data from reading provide a structured signal with a fine‐grained temporal
resolution which closely follows the sequential structure of the text. It is highly correlated with …

Sarcasm is common in social media, and people use it to express their opinions with
stronger emotions indirectly. Although it belongs to a branch of sentiment analysis …

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

Cognitive NLP systems-ie, NLP systems that make use of behavioral data-augment
traditional text-based features with cognitive features extracted from eye-movement patterns …