Computational Analysis on a Corpus of Political Satire Articles: A Theoretical and Experimental Study

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dc.contributor.advisor Delmonte, Rodolfo it_IT
dc.contributor.author Stingo, Michele <1988> it_IT
dc.date.accessioned 2016-02-10 it_IT
dc.date.accessioned 2016-05-04T11:46:02Z
dc.date.available 2016-05-04T11:46:02Z
dc.date.issued 2016-03-02 it_IT
dc.identifier.uri http://hdl.handle.net/10579/7780
dc.description.abstract Aim of this master thesis is a deeper understanding of the functioning of satire in written texts – in this specific case political satire articles – of length longer than simple sentences, in order to apply this knowledge to future computational tasks. In the first chapter there is an attempt to define satire, particularly bringing into focus the specific features of this genre. This is done by analysing the relationship with previously proposed theories on humour and their linguistic entailments, so that a line could be drawn under the grey area of definitions of humour genres, at least for what does concern the use of satire. The second chapter looks at the pros and cons of computational approaches used until now for the resolution of different tasks related to the automatic processing of humorous texts. The purpose is to outline best practises, trying to understand if it is possible to use them – consequently proper rearrangements – for more complex NLP tasks on long satiric text, in a way that allows achieving meaningful results. The third chapter is dedicated to the detailed description of the experimental part of the thesis and its outcomes. On a corpus built for that purpose and composed of 112 political satire articles manual tagging has been carried out using a reduced (and modified with new criteria, where needed) version of the Appraisal Framework (Martin & White, 2005). Then a typological classification of all voices contained in the automatically collected lexicons (one for each author) has been created using three linguistic traits – namely idiomatic, metaphorical and none. This has been done in order to assign to all the entries a feature, related to the kind of use the author did of a specific item/sequence. The final step of the experiment consists in gradual attempts to tag automatically twenty new texts (ten each) by the same authors. Eventually, by virtue of the collected data and pondered interpretations, conclusions are drawn with particular focus to further research proposals. it_IT
dc.language.iso it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Michele Stingo, 2016 it_IT
dc.title Computational Analysis on a Corpus of Political Satire Articles: A Theoretical and Experimental Study it_IT
dc.title.alternative it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Scienze del linguaggio it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Studi Linguistici e Culturali Comparati it_IT
dc.description.academicyear 2014/2015, sessione straordinaria it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 847964 it_IT
dc.subject.miur it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.subject.language INGLESE it_IT
dc.date.embargoend it_IT
dc.provenance.upload Michele Stingo (847964@stud.unive.it), 2016-02-10 it_IT
dc.provenance.plagiarycheck Rodolfo Delmonte (delmont@unive.it), 2016-02-22 it_IT


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