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Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering
Many language change studies aim for a partial revisitation, i.e., selecting survey sites from previous dialect studies. The central issue of survey site reduction, however, has often been addressed only qualitatively. Cluster analysis offers an innovative means of identifying the most representativ...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173147/ https://www.ncbi.nlm.nih.gov/pubmed/34095819 http://dx.doi.org/10.3389/frai.2021.642505 |
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author | Jeszenszky, Péter Steiner, Carina Leemann, Adrian |
author_facet | Jeszenszky, Péter Steiner, Carina Leemann, Adrian |
author_sort | Jeszenszky, Péter |
collection | PubMed |
description | Many language change studies aim for a partial revisitation, i.e., selecting survey sites from previous dialect studies. The central issue of survey site reduction, however, has often been addressed only qualitatively. Cluster analysis offers an innovative means of identifying the most representative survey sites among a set of original survey sites. In this paper, we present a general methodology for finding representative sites for an intended study, potentially applicable to any collection of data about dialects or linguistic variation. We elaborate the quantitative steps of the proposed methodology in the context of the “Linguistic Atlas of Japan” (LAJ). Next, we demonstrate the full application of the methodology on the “Linguistic Atlas of German-speaking Switzerland” (Germ.: “Sprachatlas der Deutschen Schweiz”—SDS), with the explicit aim of selecting survey sites corresponding to the aims of the current project “Swiss German Dialects Across Time and Space” (SDATS), which revisits SDS 70 years later. We find that depending on the circumstances and requirements of a study, the proposed methodology, introducing cluster analysis into the survey site reduction process, allows for a greater objectivity in comparison to traditional approaches. We suggest, however, that the suitability of any set of candidate survey sites resulting from the proposed methodology be rigorously revised by experts due to potential incongruences, such as the overlap of objectives and variables across the original and intended studies and ongoing dialect change. |
format | Online Article Text |
id | pubmed-8173147 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81731472021-06-04 Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering Jeszenszky, Péter Steiner, Carina Leemann, Adrian Front Artif Intell Artificial Intelligence Many language change studies aim for a partial revisitation, i.e., selecting survey sites from previous dialect studies. The central issue of survey site reduction, however, has often been addressed only qualitatively. Cluster analysis offers an innovative means of identifying the most representative survey sites among a set of original survey sites. In this paper, we present a general methodology for finding representative sites for an intended study, potentially applicable to any collection of data about dialects or linguistic variation. We elaborate the quantitative steps of the proposed methodology in the context of the “Linguistic Atlas of Japan” (LAJ). Next, we demonstrate the full application of the methodology on the “Linguistic Atlas of German-speaking Switzerland” (Germ.: “Sprachatlas der Deutschen Schweiz”—SDS), with the explicit aim of selecting survey sites corresponding to the aims of the current project “Swiss German Dialects Across Time and Space” (SDATS), which revisits SDS 70 years later. We find that depending on the circumstances and requirements of a study, the proposed methodology, introducing cluster analysis into the survey site reduction process, allows for a greater objectivity in comparison to traditional approaches. We suggest, however, that the suitability of any set of candidate survey sites resulting from the proposed methodology be rigorously revised by experts due to potential incongruences, such as the overlap of objectives and variables across the original and intended studies and ongoing dialect change. Frontiers Media S.A. 2021-05-20 /pmc/articles/PMC8173147/ /pubmed/34095819 http://dx.doi.org/10.3389/frai.2021.642505 Text en Copyright © 2021 Jeszenszky, Steiner and Leemann. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Jeszenszky, Péter Steiner, Carina Leemann, Adrian Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering |
title | Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering |
title_full | Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering |
title_fullStr | Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering |
title_full_unstemmed | Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering |
title_short | Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering |
title_sort | reduction of survey sites in dialectology: a new methodology based on clustering |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173147/ https://www.ncbi.nlm.nih.gov/pubmed/34095819 http://dx.doi.org/10.3389/frai.2021.642505 |
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