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Political science: Moving from numbers to words in the case of Brexit
Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Department of Political, Historical, Religious and Cultural Studies (from 2013).ORCID iD: 0000-0003-0820-8626
2020 (English)In: Statistical Semantics: Methods and Applications / [ed] Sverker Sikström & Danilo Garcia, Springer, 2020, p. 249-262Chapter in book (Refereed)
Abstract [en]

Quantitative text analysis is a growing research field in political science, whereas very few combine survey experiments with in-depth analysis of citizens’ word expressions. This chapter illustrates how a survey experiment and a latent semantic analysis are successfully combined in analyzing the 2016 EU referendum in Great Britain (Brexit). This example combines an analysis of semantic cluster approach based on experimental text data with multivariate maximum likelihood estimations. Using this approach, we are able to make finer inferences on the relationship between threat conditions and individual political behavior.

Place, publisher, year, edition, pages
Springer, 2020. p. 249-262
Keywords [en]
latent semantic analysis, voting behavior, Brexit, survey experiment
National Category
Political Science
Research subject
Political Science
Identifiers
URN: urn:nbn:se:kau:diva-78152DOI: 10.1007/978-3-030-37250-7_15Scopus ID: 2-s2.0-85089335572ISBN: 978-3-030-37249-1 (print)ISBN: 978-3-030-37250-7 (electronic)OAI: oai:DiVA.org:kau-78152DiVA, id: diva2:1439320
Projects
Sociala nätverk och val av parti: att utveckla nya språkbaserade metoder för att studera väljarbeteende
Funder
Swedish Research Council, 2017-02941Available from: 2020-06-12 Created: 2020-06-12 Last updated: 2021-02-19Bibliographically approved

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Fredén, Annika

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CiteExportLink to record
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Citation style
  • apa
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  • vancouver
  • apa.csl
  • Other style
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Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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