Logo des Repositoriums
 

Analysis of Political Debates through Newspaper Reports: Methods and Outcomes

Kurzanzeige
dc.contributor.authorLapesa, Gabriella
dc.contributor.authorBlessing, Andre
dc.contributor.authorBlokker, Nico
dc.contributor.authorDayanik, Erenay
dc.contributor.authorHaunss, Sebastian
dc.contributor.authorKuhn, Jonas
dc.contributor.authorPadó, Sebastian
dc.date.accessioned2021-05-04T09:37:31Z
dc.date.available2021-05-04T09:37:31Z
dc.date.issued2020
dc.description.abstractDiscourse network analysis is an aspiring development in political science which analyzes political debates in terms of bipartite actor/claim networks. It aims at understanding the structure and temporal dynamics of major political debates as instances of politicized democratic decision making. We discuss how such networks can be constructed on the basis of large collections of unstructured text, namely newspaper reports. We sketch a hybrid methodology of manual analysis by domain experts complemented by machine learning and exemplify it on the case study of the German public debate on immigration in the year 2015. The first half of our article sketches the conceptual building blocks of discourse network analysis and demonstrates its application. The second half discusses the potential of the application of NLP methods to support the creation of discourse network datasets.de
dc.identifier.doi10.1007/s13222-020-00344-w
dc.identifier.pissn1610-1995
dc.identifier.urihttp://dx.doi.org/10.1007/s13222-020-00344-w
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/36401
dc.publisherSpringer
dc.relation.ispartofDatenbank-Spektrum: Vol. 20, No. 2
dc.relation.ispartofseriesDatenbank-Spektrum
dc.subjectComputational Social Science
dc.subjectDiscourse Network Analysis
dc.subjectMachine Learning
dc.titleAnalysis of Political Debates through Newspaper Reports: Methods and Outcomesde
dc.typeText/Journal Article
gi.citation.endPage153
gi.citation.startPage143

Dateien

Sammlungen

Datenbank Spektrum 20(2) - Juli 2020