Political science: Moving from numbers to words in the case of Brexit

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationStatistical Semantics
Subtitle of host publicationMethods and Applications
PublisherSpringer International Publishing
Pages249-262
Number of pages14
ISBN (Electronic)9783030372507
ISBN (Print)9783030372491
DOIs
Publication statusPublished - 2020 Jan 1
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Subject classification (UKÄ)

  • Political Science

Fingerprint

Dive into the research topics of 'Political science: Moving from numbers to words in the case of Brexit'. Together they form a unique fingerprint.

Cite this