The role of defaultness and personality factors in sarcasm interpretation: evidence from eye-tracking during reading

Theorists have debated whether our ability to understand sarcasm is principally determined by the context (Gibbs, 1994; Utsumi, 2000) or by properties of the comment itself (Giora, 1997; 2003; Grice, 1975). The current research investigated an alternative view which broadens the focus on the comment itself, suggesting that mitigating a highly positive concept by using negation generates sarcastic interpretations by default (Giora et al., 2015a, 2018). In the current study, pre-tests performed on the target utterances presented in isolation established their default interpretations; novel affirmative phrases (e.g., He is the best lawyer) were interpreted literally, whereas equally novel negative counterparts (e.g., He isn’t the best lawyer) were interpreted sarcastically. In Experiment 1 (an eye-tracking study), prior context biased these utterances towards literal or sarcastic interpretations. Results showed that target utterances were easier to process in contexts supporting their default interpretations, regardless of affirmation/negation. Results from a second eye-tracking experiment suggested that readers’ tendency to interpret negative phrases sarcastically is related to their own tendency to use malicious humor. Our findings suggest that negation leads to certain ambiguous utterances receiving sarcastic interpretations by default and that this process may be further intensified by personality factors

The role of defaultness and personality factors in sarcasm interpretation: evidence from eye-tracking during reading

Theorists have debated whether our ability to understand sarcasm is principally determined by the context (Gibbs, 1994; Utsumi, 2000) or by properties of the comment itself (Giora, 1997; 2003; Grice, 1975). The current research investigated an alternative view which broadens the focus on the comment itself, suggesting that mitigating a highly positive concept by using negation generates sarcastic interpretations by default (Giora et al., 2015a, 2018). In the current study, pre-tests performed on the target utterances presented in isolation established their default interpretations; novel affirmative phrases (e.g., He is the best lawyer) were interpreted literally, whereas equally novel negative counterparts (e.g., He isn’t the best lawyer) were interpreted sarcastically. In Experiment 1 (an eye-tracking study), prior context biased these utterances towards literal or sarcastic interpretations. Results showed that target utterances were easier to process in contexts supporting their default interpretations, regardless of affirmation/negation. Results from a second eye-tracking experiment suggested that readers’ tendency to interpret negative phrases sarcastically is related to their own tendency to use malicious humor. Our findings suggest that negation leads to certain ambiguous utterances receiving sarcastic interpretations by default and that this process may be further intensified by personality factors

Irony Detection in Twitter: The Role of Affective Content

© ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Internet Technology, Vol. 16. http://dx.doi.org/10.1145/2930663.[EN] Irony has been proven to be pervasive in social media, posing a challenge to sentiment analysis systems. It is a creative linguistic phenomenon where affect-related aspects play a key role. In this work, we address the problem of detecting irony in tweets, casting it as a classification problem. We propose a novel model that explores the use of affective features based on a wide range of lexical resources available for English, reflecting different facets of affect. Classification experiments over different corpora show that affective information helps in distinguishing among ironic and nonironic tweets. Our model outperforms the state of the art in almost all cases.The National Council for Science and Technology (CONACyT Mexico) has funded the research work of Delia Irazu Hernandez Farias (Grant No. 218109/313683 CVU-369616). The work of Viviana Patti was partially carried out at the Universitat Politecnica de Valencia within the framework of a fellowship of the University of Turin cofunded by Fondazione CRT (World Wide Style Program 2). The work of Paolo Rosso has been partially funded by the SomEMBED TIN2015-71147-C2-1-P MINECO research project and by the Generalitat Valenciana under the grant ALMAMATER (PrometeoII/2014/030).Hernandez-Farias, DI.; Patti, V.; Rosso, P. (2016). Irony Detection in Twitter: The Role of Affective Content. ACM Transactions on Internet Technology. 16(3):19:1-19:24. https://doi.org/10.1145/2930663S19:119:24163Rob Abbott, Marilyn Walker, Pranav Anand, Jean E. Fox Tree, Robeson Bowmani, and Joseph King. 2011. 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Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements