@inproceedings{schatzle-booth-2019-diahclust,
title = "{D}ia{HC}lust: an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change",
author = {Sch{\"a}tzle, Christin and
Booth, Hannah},
editor = "Tahmasebi, Nina and
Borin, Lars and
Jatowt, Adam and
Xu, Yang",
booktitle = "Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4716",
doi = "10.18653/v1/W19-4716",
pages = "126--135",
abstract = "Language change is often assessed against a set of pre-determined time periods in order to be able to trace its diachronic trajectory. This is problematic, since a pre-determined periodization might obscure significant developments and lead to false assumptions about the data. Moreover, these time periods can be based on factors which are either arbitrary or non-linguistic, e.g., dividing the corpus data into equidistant stages or taking into account language-external events. Addressing this problem, in this paper we present a data-driven approach to periodization: {`}DiaHClust{'}. DiaHClust is based on iterative hierarchical clustering and offers a multi-layered perspective on change from text-level to broader time periods. We demonstrate the usefulness of DiaHClust via a case study investigating syntactic change in Icelandic, modelling the syntactic system of the language in terms of vectors of syntactic change.",
}
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<abstract>Language change is often assessed against a set of pre-determined time periods in order to be able to trace its diachronic trajectory. This is problematic, since a pre-determined periodization might obscure significant developments and lead to false assumptions about the data. Moreover, these time periods can be based on factors which are either arbitrary or non-linguistic, e.g., dividing the corpus data into equidistant stages or taking into account language-external events. Addressing this problem, in this paper we present a data-driven approach to periodization: ‘DiaHClust’. DiaHClust is based on iterative hierarchical clustering and offers a multi-layered perspective on change from text-level to broader time periods. We demonstrate the usefulness of DiaHClust via a case study investigating syntactic change in Icelandic, modelling the syntactic system of the language in terms of vectors of syntactic change.</abstract>
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%0 Conference Proceedings
%T DiaHClust: an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change
%A Schätzle, Christin
%A Booth, Hannah
%Y Tahmasebi, Nina
%Y Borin, Lars
%Y Jatowt, Adam
%Y Xu, Yang
%S Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F schatzle-booth-2019-diahclust
%X Language change is often assessed against a set of pre-determined time periods in order to be able to trace its diachronic trajectory. This is problematic, since a pre-determined periodization might obscure significant developments and lead to false assumptions about the data. Moreover, these time periods can be based on factors which are either arbitrary or non-linguistic, e.g., dividing the corpus data into equidistant stages or taking into account language-external events. Addressing this problem, in this paper we present a data-driven approach to periodization: ‘DiaHClust’. DiaHClust is based on iterative hierarchical clustering and offers a multi-layered perspective on change from text-level to broader time periods. We demonstrate the usefulness of DiaHClust via a case study investigating syntactic change in Icelandic, modelling the syntactic system of the language in terms of vectors of syntactic change.
%R 10.18653/v1/W19-4716
%U https://aclanthology.org/W19-4716
%U https://doi.org/10.18653/v1/W19-4716
%P 126-135
Markdown (Informal)
[DiaHClust: an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change](https://aclanthology.org/W19-4716) (Schätzle & Booth, LChange 2019)
ACL