Measuring Context Change to Detect Statements Violating the Overton Window

Christian Kahmann, Gerhard Heyer

2019

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.

Paper Citation

in Harvard Style

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 (IC3K 2019) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 392-396. DOI: 10.5220/0008191803920396

in Bibtex Style

@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 (IC3K 2019) - Volume 1: KDIR},
year={2019},
pages={392-396},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008191803920396},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - 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
PB - SciTePress