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Crowdsourcing dialect characterization through Twitter.

Bruno Gonçalves1, David Sánchez2

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Summary
This summary is machine-generated.

This study analyzed global Spanish language variation using Twitter data, revealing two main dialects: urban and rural. Rural Spanish further divides into distinct regional varieties.

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Area of Science:

  • Computational Linguistics
  • Sociolinguistics
  • Digital Humanities

Background:

  • Understanding language variation is crucial for linguistic research.
  • Geotagged social media data offers unprecedented scale for dialectology.
  • Previous studies have limited scope in analyzing global language patterns.

Purpose of the Study:

  • To conduct a large-scale analysis of diatopic (geographic) variation in the Spanish language.
  • To characterize global Spanish varieties using microblogging data.
  • To identify macroregions and distinct dialects within the Spanish language.

Main Methods:

  • Collected and analyzed Spanish-language Twitter messages over two years.
  • Utilized a curated list of concepts to identify linguistic features.
  • Applied cluster analysis to group messages based on lexical properties.

Main Results:

  • Identified well-defined macroregions with shared lexical characteristics.
  • Discovered a primary split into two superdialects: urban and rural Spanish.
  • Found that rural Spanish exhibits further clustering into smaller, regionally specific varieties.

Conclusions:

  • Spanish exhibits significant global variation, with a notable urban-rural divide.
  • Microblogging data is effective for large-scale dialectological studies.
  • The findings contribute to a nuanced understanding of contemporary Spanish linguistic geography.