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Quantification and Statistical Analysis of Structural Similarities in Dialectological Area-Class Maps

Bibliographic Data

ID20485075
AuthorsJonas Rumpf (Universität Ulm), Simon Pickl (0000-0003-0267-1177, Universität Augsburg, Deutsche Sprachwissenschaft, Universitätsstraße 10, 86159 Augsburg, Germany.), Stephan Elspaß (0000-0002-3870-0817, Universität Augsburg, Deutsche Sprachwissenschaft, Universitätsstraße 10, 86159 Augsburg, Germany.), Werner Konig (0000-0002-4661-5671, Universität Augsburg, Deutsche Sprachwissenschaft, Universitätsstraße 10, 86159 Augsburg, Germany.), Volker Schmidt (0000-0002-6001-9542, Universität Ulm)
Year2010
Volume18
Issue1
Pages73-100
Publication date2010-11-01
Open AccessNo
TypeARTICLE
VenueDialectologia et Geolinguistica (JOURNAL)
Journal identifiersISSN: 0942-4040 • E-ISSN: 1867-0903
PublisherWalter de Gruyter GmbH (PUBLISHER • DE)
DOI10.1515/dig.2010.005
OpenAlexW2005883273
LanguageEN
Citations received3
References cited4

Dialect atlases comprise considerable numbers of linguistic feature maps, i.e. dialect maps representing one linguistic feature each. Large amounts of data like these are often difficult to handle. This article presents a new quantitative method for the automatic analysis of such large corpora of linguistic feature maps. It makes use of geographical similarities between single maps to establish a system of criteria for structural relatedness. Furthermore, it employs statistical techniques to test whether given linguistic relations between the maps coincide significantly with structural relations. To achieve this, each underlying point-symbol map is converted into an area-class map (with all the original information still available). These area-class maps yield additional information regarding their structural composition. Cluster analysis is then employed to obtain groupings of similar maps. Such groupings facilitate the search for language-internal factors that influence the geographical distribution of linguistic variants, as the relevance of any given linguistic parameter for spatial patterns can be tested using statistical methods. Moreover, language-external factors, such as topographical conditions, can be tested in the same way. Thus, this new method allows for a profound and substantiated investigation of the regularities that can be found in the geographical distributions of linguistic variants

Linguistics · Natural language processing · Computer Science · Language and cultural evolution · Linguistic Variation and Morphology · Linguistics and Cultural Studies · Mathematics · Artificial Intelligence

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Citations per year0.2
Citation span2011 - 2026 (16)
Highly citedNo

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