'The more populism types you know, the better political scientist you are?' Machine-learning based meta-analysis of populism types in the political science literature.

Autor:	Naxera, Vladimír, Kaše, Vojtěch, Stulík, Ondřej
Předmět:	POPULISM POLITICAL science POLITICAL scientists META-analysis DOCUMENT classification
Zdroj:	Journal of Contemporary European Studies; Dec2024, Vol. 32 Issue 4, p1057-1074, 18p
Abstrakt:	This text builds on existing debates on types of populism in contemporary political science literature. Our premise is that with new types of populism emerging in the debate, and with the significantly increasing number of texts dealing with populism, the types are being hollowed out. Using a dataset consisting of a total of 539 texts published between 2011 and 2020 containing the keyword populism and using a machine-learning based classification model of concordance data, we show that (1.) ambiguities and confusions among the different types of populism become more prominent over the study period, categories become emptier and their usefulness for classification decreases, and (2.) the only stable and consensually defined type in the long run is right-wing populism. We conclude by recommending to depart from creating classifications of types of populism based on specific ideological or non-ideological features and to keep these levels (populism and other features) – within analysis – separate. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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