Multi-National Topics Maps for Parliamentary Debate Analysis

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dc.contributor.authorSchaal, Markus
dc.contributor.authorDavis, Enno
dc.contributor.authorMueller, Roland M.
dc.date.accessioned2021-12-24T17:45:03Z
dc.date.available2021-12-24T17:45:03Z
dc.date.issued2022-01-04
dc.description.abstractIn recent years, automated political text processing became an indispensable requirement for providing automatic access to political debate. During the Covid-19 worldwide pandemic, this need became visible not only in social sciences but also in public opinion. We provide a path to operationalize this need in a multi-lingual topic-oriented manner. Using a publicly available data set consisting of parliamentary speeches, we create a novel process pipeline to identify a good reference model and to link national topics to the cross-national topics. We use design science research to create this process pipeline as an artifact.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.366
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79700
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Analytics, Data Mining and Machine Learning for Social Media
dc.subjectcross-country
dc.subjectlatent dirichlet allocation
dc.subjectmulti-lingual
dc.subjectparliamentary speech
dc.subjectprobabilistic topic modelling
dc.titleMulti-National Topics Maps for Parliamentary Debate Analysis
dc.type.dcmitext

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