This book presents a theory of long humorous texts based on a revision and an upgrade of the General Theory of Verbal Humour (GTVH), a decade after its first proposal. The theory is informed by current research in psycholinguistics and cognitive science. It is predicated on the fact that there are humorous mechanisms in long texts that have no counterpart in jokes. The book includes a number of case studies, among them Oscar Wilde's Lord Arthur Savile's Crime and Allais' story Han Rybeck. A ground-breaking discussion of the quantitative distribution of humor in select texts is presented.

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Humorous Texts: A Semantic and Pragmatic Analysis

The relationship between context incongruity and sarcasm has been studied in linguistics. We present a computational system that harnesses context incongruity as a basis for sarcasm detection. Our statistical sarcasm classifiers incorporate two kinds of incongruity features: explicit and implicit. We show the benefit of our incongruity features for two text forms tweets and discussion forum posts. Our system also outperforms two past works (with Fscore improvement of 10-20%). We also show how our features can capture intersentential incongruity.

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Harnessing Context Incongruity for Sarcasm Detection

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 text. Beginning with an approach that used speech-based features, automatic sarcasm detection has witnessed great interest from the sentiment analysis community. This article is a compilation of past work in automatic sarcasm detection. We observe three milestones in the research so far: semi-supervised pattern extraction to identify implicit sentiment, use of hashtag-based supervision, and incorporation of context beyond target text. In this article, we describe datasets, approaches, trends, and issues in sarcasm detection. We also discuss representative performance values, describe shared tasks, and provide pointers to future work, as given in prior works. In terms of resources to understand the state-of-the-art, the survey presents several useful illustrations—most prominently, a table that summarizes past papers along different dimensions such as the types of features, annotation techniques, and datasets used.

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Automatic Sarcasm Detection: A Survey

Detecting Sarcasm from Paralinguistic Cues: Anatomic and Cognitive Correlates in Neurodegenerative Disease

Jocular mockery, (dis)affiliation, and face

Multimodal markers of irony and sarcasm

http://www.lenguasvivas.org/campus/files/0_30/ironyindiscourse.pdf

Reactions to irony in discourse: evidence for the least disruption principle

Much of what we think we know about the performance of humor relies on our intuitions about prosody (e.g., “it's all about timing”); however, this has never been empirically tested. Thus, the central question addressed in this article is whether speakers mark punch lines in jokes prosodically and, if so, how. To answer this question, this article unites both the recently emerged research agenda grounding spoken discourse analysis in the precision and verifiability of acoustic analysis and a research agenda within the field of discourse and humor focused on the “performance” of humorous narratives. This article presents an analysis of a relatively simple form: the joke or short humorous narrative. The starting point of this analysis is the folk theory of joke-telling. Through instrumental measurement of pitch, volume, and speech rate, this study shows that, contrary to the folk theory of joke-delivery, punch lines are not delivered significantly louder than the preceding text, but rather at a significantly...

/pdf/prosodic-markers-of-saliency-in-humorous-narratives-38swi8qux5.pdf

Jodi Eisterhold

Papers

Multimodal markers of irony and sarcasm

Reactions to irony in discourse: evidence for the least disruption principle

Prosodic Markers of Saliency in Humorous Narratives