2026-07-22T06:50:49Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:14574 2024-03-06T10:31:29Z ddc:004 open_access

Exploring Causal Relationships Among Emotional and Topical Trajectories in Political Text Data Baumann, Andreas Hofmann, Klaus Kern, Bettina Marakasova, Anna Neidhardt, Julia Wissik, Tanja time-series clustering Granger causality topical stability emotion political discourse We explore relationships between dynamics of emotion (arousal and valence) and topical stability in political discourse in two diachronic corpora of Austrian German. In doing so, we assess interactions among emotional and topical dynamics related to political parties as well as interactions between two different domains of discourse: debates in the parliament and journalistic media. Methodologically, we employ unsupervised techniques, time-series clustering and Granger-causal modeling to detect potential interactions. We find that emotional and topical dynamics in the media are only rarely a reflex of dynamics in parliamentary discourse. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Andreas Baumann and Klaus Hofmann and Bettina Kern and Anna Marakasova and Julia Neidhardt and Tanja Wissik 2021 Is Part Of OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.LDK.2021.38 urn:nbn:de:0030-drops-145740 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.38 eng https://creativecommons.org/licenses/by/4.0/legalcode