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1
Multi-National Topics Maps for Parliamentary Debate Analysis
Schaal, Markus
;
Davis, Enno
;
Mueller, Roland M.
. - 2022
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.
Keyword:
cross-country
;
Data Analytics
;
Data Mining and Machine Learning for Social Media
;
latent dirichlet allocation
;
multi-lingual
;
parliamentary speech
;
probabilistic topic modelling
URL:
http://hdl.handle.net/10125/79700
https://doi.org/10.24251/HICSS.2022.366
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