Populism and emotions : a comparative study using machine learning

CAIANI, Manuela; DI COCCO, Jessica

doi:10.1017/ipo.2023.8

Populism and emotions : a comparative study using machine learning

dc.contributor.author	CAIANI, Manuela
dc.contributor.author	DI COCCO, Jessica
dc.date.accessioned	2024-05-07T07:37:22Z
dc.date.available	2024-05-07T07:37:22Z
dc.date.issued	2023
dc.description	Published online: 11 May 2023	en
dc.description.abstract	This study aims to unpack the mobilization of emotions in the political discourse of populist and non-populist parties and above all, across ‘varieties of populism’ (right wing vs. left wing or hybrid). Is there an empirical connection between emotions and populism? Are all types of populisms alike with regards to the emotional appeals within their political discourse? Focusing on Italy as a crucial case for populist communication and using a novel methodological approach based on supervised machine learning, it systematically investigates the intensity and trends of specific emotions in political discourses (institutional and informal, i.e. leaders’ speeches) of all Italian political parties over the last 20 years, for a corpus of more than 13,000 sentences analysed. The findings confirm that (i) populists tend to use more (and a broader repertoire of) emotional appeals than non-populist parties; however (ii) overall, there is an increase in the use of these appeals in the Italian political party discourse over time, especially in terms of negative emotions; and, most importantly, (iii) different types of emotions are mobilized by different types of populisms. Right wing populism mainly uses negative emotions while left wing or hybrid populism employs positive emotional appeals. The communication arena (party manifestoes vs. speeches) nevertheless does matter in the degree and types of emotions mobilized by political actors. This study identifies important implications for research on emotional appeals in politics, populist communication and political campaigning, and populist contagion from an emotion-based perspective.	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Italian Political Science Review/Rivista Italiana di Scienza Politica, 2023, Vol. 53, No. 3, pp. 351-366	en
dc.identifier.doi	10.1017/ipo.2023.8
dc.identifier.endpage	366	en
dc.identifier.issn	0048-8402
dc.identifier.issn	2057-4908
dc.identifier.issue	3	en
dc.identifier.startpage	351	en
dc.identifier.uri	https://hdl.handle.net/1814/76848
dc.identifier.volume	53	en
dc.language.iso	en	en
dc.orcid.upload	true	*
dc.publisher	Cambridge University Press	en
dc.relation.ispartof	Italian Political Science Review	en
dc.relation.ispartof	Rivista Italiana di Scienza Politica	it
dc.rights	info:eu-repo/semantics/openAccess	en
dc.rights.license	Attribution 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.title	Populism and emotions : a comparative study using machine learning	en
dc.type	Article	en
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