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A two-step procedure to identify stance constructions in discourse from political blogs
Lancaster University, UK ; Lund University.ORCID iD: 0000-0002-8998-3618
Lund University.ORCID iD: 0000-0002-7240-9003
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS)ORCID iD: 0000-0002-0519-2537
2019 (English)In: Corpora, ISSN 1749-5032, E-ISSN 1755-1676, Vol. 14, no 3Article in journal (Refereed) Accepted
Abstract [en]

The Brexit Blog Corpus (BBC) is a collection of texts extracted from political blogs, which, in a recent study, was annotated according to a cognitive-functional stance framework by two independent annotators (Annotator A and B) using semantic criteria (Simaki et al. 2017). The goal was to label the stance or stances taken based on the overall meaning of a set of utterances. The annotators were not instructed to identify the lexical forms that were used to express the stances. In this study, we make use of those stance labelled utterances as a springboard to approach stance-taking in text from the opposite point of view, namely from how stance is realised through language. Our aim is to provide a description of the specific lexical elements used to express six stance categories, i.e., CONTRARIETY, HYPOTHETICALITY,  NECESSITY, PREDICTION, SOURCE OF KNOWLEDGE, and UNCERTAINTY. To this end, we followed a two-step experimental procedure. First, we performed a quantitative analysis of the stance labelled utterances in order to identify the lexical realisations of each stance category. Second, we carried out a meta-annotation of the data. Annotator B was instructed to single out the actual lexical forms of the constructions that triggered his semantic stance category decisions. This meta-annotation procedure made it possible for us to sift out the most salient lexical realisations of the constructions of each of the six category types on the basis of the qualitative assessments made by Annotator B. We then compared the results of the quantitative and the qualitative approaches, and we present a list of shared stance expressions for each stance category type.

Place, publisher, year, edition, pages
2019. Vol. 14, no 3
Keywords [en]
stance-taking, social media text analysis, stance construction, meta-annotation, corpus annotation, Brexit, Blogs
National Category
General Language Studies and Linguistics
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-79384OAI: oai:DiVA.org:lnu-79384DiVA, id: diva2:1276674
Projects
StaViCTA
Part of project
Advances in the description and explanation of stance in discourse using visual and computational text analytics - StaViCTA, Swedish Research Council
Funder
Swedish Research Council, 2012-5659
Note

TO BE PUBLISHED!!

Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-09-04

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Kerren, Andreas

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