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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Geolinguistic techniques in 2025: An introduction

Authors: SHIRAI, Satoko;

Geolinguistic techniques in 2025: An introduction

Abstract

This paper introduces the special feature, Geolinguistic Techniques in 2025. It first outlines the nature and significance of maps used in geolinguistics and linguistic/dialect geography, emphasizing their role as interpretive tools that help uncover patterns and histories of linguistic variation. The article distinguishes geolinguistic maps from other types, such as data maps, typological maps, and distribution maps, while highlighting their potential to reveal the historical and social dynamics of language variation. With the advancement of Geographic Information System (GIS), map production has become more flexible and accessible, though ongoing technical developments can be challenging for researchers unfamiliar with digital tools. This special feature aims to support researchers in producing meaningful geolinguistic maps and to foster further methodological development and accessibility in geolinguistic research, providing a practical manual and a case study.

Related Organizations
Keywords

data map, geolinguistics, typological map, Geographic Information System (GIS), linguistic map

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green