Several NLP studies address the problem of figurative language, but among non-literal phenomena, they have neglected exaggeration. This paper presents a first computational approach to this figure of speech. We explore the possibility to automatically detect exaggerated sentences. First, we introduce HYPO, a corpus containing overstatements (or hyperboles) collected on the web and validated via crowdsourcing. Then, we evaluate a number of models trained on HYPO, and bring evidence that the task of hyperbole identification can be successfully performed based on a small set of semantic features.
A Computational Exploration of Exaggeration / Troiano, Enrica; Strapparava, Carlo; Gözde, Özbal; Tekiroglu, Serra Sinem. - ELETTRONICO. - (2018), pp. 3296-3304. (Intervento presentato al convegno 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP-2018) tenutosi a Brussels, Belgium nel October 31 - November 4, 2018).
A Computational Exploration of Exaggeration
Carlo Strapparava;Gözde Özbal;Serra Tekiroglu
2018-01-01
Abstract
Several NLP studies address the problem of figurative language, but among non-literal phenomena, they have neglected exaggeration. This paper presents a first computational approach to this figure of speech. We explore the possibility to automatically detect exaggerated sentences. First, we introduce HYPO, a corpus containing overstatements (or hyperboles) collected on the web and validated via crowdsourcing. Then, we evaluate a number of models trained on HYPO, and bring evidence that the task of hyperbole identification can be successfully performed based on a small set of semantic features.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
