Sarcasm is a form of speech act in which the speakers convey their message in an implicit way. The inherently ambiguous nature of sarcasm sometimes makes it hard even for humans to decide whether an utterance is sarcastic or not. Recognition of sarcasm can benefit many sentiment analysis NLP applications, such as review summarization, dialogue systems and review ranking systems. In this paper w...

Sarcasm is a form of speech in which speakers say the opposite of what they truly mean in order to convey a strong sentiment. In other words, ”Sarcasm is the giant chasm between what I say, and the person who doesn’t get it.”. In this paper we present the novel task of sarcasm interpretation, defined as the generation of a non-sarcastic utterance conveying the same message as the original sarca...

To avoid a sarcastic message being understood in its unintended literal meaning, in microtexts such as messages on Twitter.com sarcasm is often explicitly marked with a hashtag such as ‘#sarcasm’. We collected a training corpus of about 406 thousand Dutch tweets with hashtag synonyms denoting sarcasm. Assuming that the human labeling is correct (annotation of a sample indicates that about 90% o...

Sarcasm is a sophisticated form of speech used to convey message other than the apparent one. To date, there are numerous papers that have discussed idea automatic sarcasm detection and how it could be for sentiment analysis improvement. The objective this paper provide non-experts with comprehensive overview state research in field main findings regarding detection. Therefore, paper, we survey...

Based on the assumption that comment with positive sentimental polarity to a negative issue has high probability to be a sarcasm, we propose a simple yet efficient method to collect sarcastic textual data by crowdsourcing with social media and merging game with a purpose approach. Taking advantage of Facebook's reaction button, posts triggering strong negative emotion are collected. Next, by us...

This paper presents a machine learning approach to sarcasm detection on Twitter in two languages – English and Czech. Although there has been some research in sarcasm detection in languages other than English (e.g., Dutch, Italian, and Brazilian Portuguese), our work is the first attempt at sarcasm detection in the Czech language. We created a large Czech Twitter corpus consisting of 7,000 manu...

Unlike their English-speaking counterparts, Japanese children with high-functioning autism spectrum disorders (HFASDs) perform as well as typically developing (TD) children in comprehending metaphor, despite lacking 1st order theory of mind (ToM) reasoning. Additionally, although Japanese sarcasm and "indirect reproach" appear theoretically to need 2nd order ToM reasoning, HFASD children withou...

Two subtests—Sarcasm Comprehension and Metaphor Comprehension—of Gardner and Brownell’s (1986) Right Hemisphere Communication Battery, adapted to Hebrew, were administered to 27 right-brain-damaged (RBD) patients, 31 left-brain-damaged (LBD) patients, and 21 age-matched normal controls. RBD patients tended to score somewhat lower than LBD patients on Sarcasm Comprehension METAPHOR AND SYMBOL, 1...