Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility

Christian Kahmann, Andreas Niekler, Gerhard Heyer

Abstract

Terms in diachronic text corpora may exhibit a high degree of semantic dynamics that is only partially captured by the common notion of semantic change. The new measure of context volatility that we propose models the degree by which terms change context in a text collection over time. The computation of context volatility for a word relies on the significance-values of its co-occurrent terms and the corresponding co-occurrence ranks in sequential time spans. We define a baseline and present an efficient computational approach in order to overcome problems related to computational issues in the data structure. Results are evaluated both, on synthetic documents that are used to simulate contextual changes, and a real example based on British newspaper texts. The data and software are avaiable at https://git.informatik.uni-leipzig.de/mam10cip/KDIR.git.

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Paper Citation


in Harvard Style

Kahmann C., Niekler A. and Heyer G. (2017). Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-271-4, pages 135-143. DOI: 10.5220/0006574001350143


in Bibtex Style

@conference{kdir17,
author={Christian Kahmann and Andreas Niekler and Gerhard Heyer},
title={Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2017},
pages={135-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006574001350143},
isbn={978-989-758-271-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility
SN - 978-989-758-271-4
AU - Kahmann C.
AU - Niekler A.
AU - Heyer G.
PY - 2017
SP - 135
EP - 143
DO - 10.5220/0006574001350143