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Autor/inn/enKovaz, David; Kreuz, Roger J.; Riordan, Monica A.
TitelDistinguishing Sarcasm from Literal Language: Evidence from Books and Blogging
QuelleIn: Discourse Processes: A Multidisciplinary Journal, 50 (2013) 8, S.598-615 (18 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0163-853X
DOI10.1080/0163853X.2013.849525
SchlagwörterLanguage Usage; Electronic Publishing; Phrase Structure; Negative Attitudes; Books; Discourse Analysis; Cues; Computer Mediated Communication; Stereotypes; Computational Linguistics; Comprehension; Accuracy; Language Processing; Regression (Statistics); Comparative Analysis; Pragmatics
AbstractSarcasm production and comprehension have been traditionally described in terms of pragmatic factors. Lexical cues have received less attention, but they may be important potential indicators. A major obstacle to examining such features is determining sarcastic intent. One solution is to analyze statements explicitly marked as being sarcastic. This study examined Twitter postings marked with #sarcasm as well as dialog from Google Books containing the phrase "said sarcastically." We used word counting and part-of-speech tagging to compare specific lexical features of the explicitly-marked sarcastic statements to statements by the same author not marked as sarcastic. Our results broadly support the Lexical Cues Hypothesis--certain word-level cues, such as interjections and positive affect terms, are stereotypic of sarcasm. A model incorporating these features performed comparably to human raters in making sarcastic versus nonsarcastic judgments. This finding shows promise for future work toward automatically identifying sarcasm in text. (As Provided).
AnmerkungenRoutledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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