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Evaluating stance-annotated sentences from the Brexit Blog Corpus: A quantitative linguistic analysis
Lancaster University,UK ; Lund University. (ISOVIS)ORCID-id: 0000-0002-8998-3618
Lund University.ORCID-id: 0000-0002-7240-9003
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). (ISOVIS)ORCID-id: 0000-0002-0519-2537
2018 (Engelska)Ingår i: ICAME Journal/International Computer Archive of Modern English, ISSN 0801-5775, E-ISSN 1502-5462, Vol. 42, nr 1, s. 133-166Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This paper offers a formally driven quantitative analysis of stance-annotated sentences in the Brexit Blog Corpus (BBC). Our goal is to highlight linguistic features that determine the formal profiles of six stance categories (contrariety, hypotheticality, necessity, prediction, source of knowledge and uncertainty) in a subset of the BBC. The study has two parts: firstly, it examines a large number of formal linguistic features that occur in the sentences in order to describe the specific characteristics of each category, and secondly, it compares characteristics in the entire data set in order to determine linguistic similarities throughout the data set. We show that among the six stance categories in the corpus, contrariety and necessity are the most discriminative ones, with the former using longer sentences, more conjunctions, more repetitions and shorter forms than the sentences expressing other stances. The latter has longer lexical forms but shorter sentences, which are syntactically more complex. We show that stance in our data set is expressed in sentences with around 21 words per sentence. The sentences consist mainly of alphabetical characters forming a varied vocabulary without special forms, such as digits or special characters.

Ort, förlag, år, upplaga, sidor
De Gruyter Open, 2018. Vol. 42, nr 1, s. 133-166
Nyckelord [en]
stance-taking, corpus annotation, political blog text, statistical analysis, formal features
Nationell ämneskategori
Språkteknologi (språkvetenskaplig databehandling) Studier av enskilda språk
Forskningsämne
Datavetenskap, Informations- och programvisualisering
Identifikatorer
URN: urn:nbn:se:lnu:diva-70768DOI: 10.1515/icame-2018-0007OAI: oai:DiVA.org:lnu-70768DiVA, id: diva2:1182076
Projekt
StaViCTA
Forskningsfinansiär
Vetenskapsrådet, 2012-5659Tillgänglig från: 2018-02-12 Skapad: 2018-02-12 Senast uppdaterad: 2018-10-17Bibliografiskt granskad

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Simaki, VasilikiParadis, CaritaKerren, Andreas

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Simaki, VasilikiParadis, CaritaKerren, Andreas
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ICAME Journal/International Computer Archive of Modern English
Språkteknologi (språkvetenskaplig databehandling)Studier av enskilda språk

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