{"type":"ScholarlyArticle","title":"Do We Criticise (and Laugh) in the Same Way? Automatic Detection of Multi-Lingual Satirical News in Twitter","authors":[{"name":"Francesco Barbieri","slug":"francesco-barbieri","given":"Francesco","family":"Barbieri","affiliation":"Universitat Pompeu Fabra , Barcelona , Spain"},{"name":"Francesco Ronzano","slug":"francesco-ronzano","given":"Francesco","family":"Ronzano","affiliation":"Universitat Pompeu Fabra , Barcelona , Spain"},{"name":"Horacio Saggion","slug":"horacio-saggion","given":"Horacio","family":"Saggion","affiliation":"Universitat Pompeu Fabra , Barcelona , Spain"}],"abstract":"During the last few years, the investigation of methodologies to automatically detect and characterise the figurative traits of textual contents has attracted a growing interest. Indeed, the capability to correctly deal with figurative language and more specifically with satire is fundamental to build robust approaches in several sub-fields of Artificial Intelligence including Sentiment Analysis and Affective Computing. In this paper we investigate the automatic detection of Tweets that advertise satirical news in English, Spanish and Italian. To this purpose we present a system that models Tweets from different languages by a set of language independent features that describe lexical, semantic and usage-related properties of the words of each Tweet. We approach the satire identification problem as binary classification of Tweets as satirical or not satirical messages. We test the performance of our system by performing experiments of both monolingual and cross-language classifications, evaluating the satire detection effectiveness of our features.Our system outperforms a word-based baseline and it is able to recognise if a news in Twitter is satirical or not with good accuracy. Moreover, we analyse the behaviour of the system across the different languages, obtaining interesting results.","doi":null,"url":"https://ijcai.org/proceedings/2015/175","pdf":"https://ijcai.org/proceedings/2015/0175.pdf","markdown":"https://ijcai.org/proceedings/2015/175.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/175","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Natural Language Processing","track":"Main Track","number":175,"pages":{"first":1215,"last":1220},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Baccianella et al., 2010] Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 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