Text mining methods for measuring the coherence of party manifestos for the German federal elections from 1990 to 2021

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DC Field	Value	Language
dc.contributor.author	Jentsch, Carsten	-
dc.contributor.author	Mammen, Enno	-
dc.contributor.author	Müller, Henrik	-
dc.contributor.author	Rieger, Jonas	-
dc.contributor.author	Schötz, Christof	-
dc.date.accessioned	2021-09-14T11:45:51Z	-
dc.date.available	2021-09-14T11:45:51Z	-
dc.date.issued	2021-09-14	-
dc.identifier.uri	http://hdl.handle.net/2003/40491	-
dc.identifier.uri	https://doi.org/10.17877/de290r-22363	-
dc.language.iso	en	de
dc.relation.ispartofseries	DoCMA Working Paper;8	en
dc.subject	Poisson reduced-rank models	en
dc.subject	latent Dirichlet allocation	en
dc.subject	CDU	de
dc.subject	CSU	de
dc.subject	union	en
dc.subject	SPD	de
dc.subject	Grüne	de
dc.subject	FDP	de
dc.subject	Linke	de
dc.subject	Kenia	de
dc.subject	Jamaica	en
dc.subject	Ampel	de
dc.subject	Deutschland	de
dc.subject	R2G	de
dc.subject	coalition	en
dc.subject.ddc	004	-
dc.subject.ddc	070	-
dc.subject.ddc	310	-
dc.title	Text mining methods for measuring the coherence of party manifestos for the German federal elections from 1990 to 2021	de
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access	-
eldorado.secondarypublication	false	de
Appears in Collections:	DoCMA Working Papers

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