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Authors: Christian Kahmann and Gerhard Heyer

Affiliation: Department for Natural Language Processing, Leipzig University, Augustusplatz 10, Leipzig and Germany

ISBN: 978-989-758-382-7

Keyword(s): Text Mining, Humanities, Semantic Change.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Context Discovery ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: The so-called Overton window describes the phenomenon that political discourse takes place in a narrow window of terms that reflect the public consensus of acceptable opinions on some topic. In this paper we present a novel NLP approach to identify statements in a collection of newspaper articles that shift the borders of the Overton window at some period of time, and apply it on German newspaper texts detecting extreme statements about the refugee crisis in Germany.

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Paper citation in several formats:
Kahmann, C. and Heyer, G. (2019). Measuring Context Change to Detect Statements Violating the Overton Window.In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-382-7, pages 392-396. DOI: 10.5220/0008191803920396

@conference{kdir19,
author={Christian Kahmann. and Gerhard Heyer.},
title={Measuring Context Change to Detect Statements Violating the Overton Window},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2019},
pages={392-396},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008191803920396},
isbn={978-989-758-382-7},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Measuring Context Change to Detect Statements Violating the Overton Window
SN - 978-989-758-382-7
AU - Kahmann, C.
AU - Heyer, G.
PY - 2019
SP - 392
EP - 396
DO - 10.5220/0008191803920396

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