How speakers alert addressees to multiple meanings

Givoni, Shir; Giora, Rachel; Bergerbest, Dafna

doi:10.1016/j.pragma.2012.11.011

Cited by 40 publications

(32 citation statements)

References 23 publications

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“…Following Giora et al (2010Giora et al ( , 2013 and Givoni et al (2013), negation is viewed here as a low-salience marker, highlighting a concept's meanings low on salience via rejecting them. As a low-salience marker, negation may prompt low salience metaphorical features (as shown in Giora, 2006;Giora et al, 2010Giora et al, , 2013.…”

Section: Discussionmentioning

confidence: 99%

“…Consequently, they will be read faster in contexts strongly biasing them toward their sarcastic than toward their (equally strongly biased) literal interpretation. Although a complete set of factors constraining such constructions is yet to be explored, some of our recent studies indicate that negation (among other low-salience markers) plays a crucial role in highlighting low-salience interpretations by default (on low-salience marking, see Givoni, Giora, & Bergerbest, 2013; on negation as highlighting novel, nonliteral interpretations by default, see Giora et al, 2010Giora et al, , 2013.…”

Section: Predictionsmentioning

confidence: 99%

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Default Sarcastic Interpretations: On the Priority of Nonsalient Interpretations

Giora

Drucker

Fein

et al. 2014

Discourse Processes

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Findings from five experiments support the view that negation generates sarcastic utterance-interpretations by default. 1 When presented in isolation, novel negative constructions ("Punctuality is not his forte," "Thoroughness is not her most distinctive feature"), free of semantic anomaly or internal incongruity, were interpreted sarcastically and rated as sarcastic compared to their novel affirmative counterparts (Experiments 1 and 3). In strongly supportive contexts, they were processed faster when biased toward their noncoded (nonsalient) sarcastic interpretation than toward their noncoded but (salience-based) literal interpretation (Experiments 2 and 4). Experiment 5 reduces the possibility that it is structural markedness rather than negation that prompts nonliteralness. Such findings, attesting to the priority of sarcastic interpretations, are unaccountable by any contemporary processing model, including the Graded Salience Hypothesis.

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Section: Discussionmentioning

confidence: 99%

Section: Predictionsmentioning

confidence: 99%

Default Sarcastic Interpretations: On the Priority of Nonsalient Interpretations

Giora

Drucker

Fein

et al. 2014

Discourse Processes

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“…Research on the use of different hashtags (particularly #irony, #sarcasm and #not) could be useful in order to investigate if they can be low-salience cues [33], i.e. if Twitter users may use these kinds of markers in order to highlight their non-literal intention.…”

Section: Irony Sarcasm Et Similiamentioning

confidence: 99%

Figurative messages and affect in Twitter: Differences between #irony, #sarcasm and #not

Sulis

Farías

Rosso

et al. 2016

Knowledge-Based Systems

148

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The use of irony and sarcasm has been proven to be a pervasive phenomenon in social media posing a challenge to sentiment analysis systems. Such devices, in fact, can influence and twist the polarity of an utterance in different ways. A new dataset of over 10,000 tweets including a high variety of figurative language types, manually annotated with sentiment scores, has been released in the context of the task 11 of SemEval-2015.In this paper, we propose an analysis of the tweets in the dataset to investigate the open research issue of how separated figurative linguistic phenomena irony and sarcasm are, with a special focus on the role of features related to the multi-faceted affective information expressed in such texts. We considered for our analysis tweets tagged with #irony and #sarcasm, and also the tag #not, which has not been studied in depth before. A distribution and correlation analysis over a set of features, including a wide variety of psycholinguistic and emotional features, suggests arguments for the separation between irony and sarcasm. The outcome is a novel set of sentiment, structural and psycholinguistic features evaluated in binary classification experiments. We report about classification experiments carried out on a previously used corpus for #irony vs #sarcasm. We outperform in terms of F-measure the state-of-the-art results on this dataset. Overall, our results confirm the difficulty of the task, but introduce new datadriven arguments for the separation between #irony and #sarcasm. Interestingly, #not 1 Corresponding author: sulis@di.unito.it. 2 The first two authors equally contributed to this work.

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“…According to Givoni et al (2013), a number of markers play a significant role in prompting low-salience meanings and interpretations, whether literal or nonliteral. Take literally for example.…”

Section: Discussionmentioning

confidence: 99%

“…According to lexicon-based and pragmatically oriented models including the graded salience hypothesis, the answer to all these questions must be in the affirmative, since it should involve its negative salience-based interpretation initially, in spite of its contextual incompatibility. In contrast, according to the view of negation as a low-salience marker Giora et al 2010;Givoni et al 2013), highlighting meanings and interpretations low on salience, the answer to these questions must be in the negative. Unlike affirmative sarcasm, this view predicts that, in processing negative sarcasm, it is the nonsalient sarcastic interpretation that should be tapped initially and directly, without having to activate the salience-based (often literal) interpretation first.…”

Section: Negative Sarcasm-on the Priority Of Nonsalient Interpretationsmentioning

confidence: 99%

Negation and Polarity: Experimental Perspectives

Larrivée¹,

李²

2016

Language, Cognition, and Mind

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How speakers alert addressees to multiple meanings

Cited by 40 publications

References 23 publications

Default Sarcastic Interpretations: On the Priority of Nonsalient Interpretations

Default Sarcastic Interpretations: On the Priority of Nonsalient Interpretations

Figurative messages and affect in Twitter: Differences between #irony, #sarcasm and #not

Negation and Polarity: Experimental Perspectives

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