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 language | English |
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Title of host publication | Statistical Semantics |
Subtitle of host publication | Methods and Applications |
Publisher | Springer International Publishing |
Pages | 249-262 |
Number of pages | 14 |
ISBN (Electronic) | 9783030372507 |
ISBN (Print) | 9783030372491 |
DOIs | |
Publication status | Published - 2020 Jan 1 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© Springer Nature Switzerland AG 2020.
Subject classification (UKÄ)
- Political Science