Multi-National Topics Maps for Parliamentary Debate Analysis Schaal, Markus Davis, Enno Mueller, Roland M. 2021-12-24T17:45:03Z 2021-12-24T17:45:03Z 2022-01-04
dc.description.abstract In 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.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.366
dc.identifier.isbn 978-0-9981331-5-7
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Data Analytics, Data Mining and Machine Learning for Social Media
dc.subject cross-country
dc.subject latent dirichlet allocation
dc.subject multi-lingual
dc.subject parliamentary speech
dc.subject probabilistic topic modelling
dc.title Multi-National Topics Maps for Parliamentary Debate Analysis
dc.type.dcmi text
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