In this paper, we present initial experiments in the recognition of deceptive language. We introduce three data sets of true and lying texts collected for this purpose, and we show that automatic classification is a viable technique to distinguish between truth and falsehood as expressed in language. We also introduce a method for class-based feature analysis, which sheds some light on the features that are characteristic for deceptive text.
The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language / Mihalcea, Rada; Strapparava, Carlo. - (2009), pp. 309-312. (Intervento presentato al convegno 47th annual meeting of the Association of Computational Linguistics (ACL-09) tenutosi a Singapore, Singapore nel 02/08/2009 - 07/08/2009).
The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language
Carlo Strapparava
2009-01-01
Abstract
In this paper, we present initial experiments in the recognition of deceptive language. We introduce three data sets of true and lying texts collected for this purpose, and we show that automatic classification is a viable technique to distinguish between truth and falsehood as expressed in language. We also introduce a method for class-based feature analysis, which sheds some light on the features that are characteristic for deceptive text.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
