mlsanityData to 7 Oct 2026

Global Syntactic Variation in Seven Languages: Towards a Computational Dialectology

arXiv 2104.01306 ↗First posted 3 Apr 2021cs.CLcited by 11

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Abstract (arXiv)

The goal of this paper is to provide a complete representation of regional linguistic variation on a global scale. To this end, the paper focuses on removing three constraints that have previously limited work within dialectology/dialectometry. First, rather than assuming a fixed and incomplete set of variants, we use Computational Construction Grammar to provide a replicable and falsifiable set of syntactic features. Second, rather than assuming a specific area of interest, we use global language mapping based on web-crawled and social media datasets to determine the selection of national varieties. Third, rather than looking at a single language in isolation, we model seven major languages together using the same methods: Arabic, English, French, German, Portuguese, Russian, and Spanish. Results show that models for each language are able to robustly predict the region-of-origin of held-out samples better using Construction Grammars than using simpler syntactic features. These global-scale experiments are used to argue that new methods in computational sociolinguistics are able to provide more generalized models of regional variation that are essential for understanding language variation and change at scale.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 7 of its 83 references that are in the map. First posted on arXiv 3 Apr 2021.

Builds on

7 of 83 references.

References · 7

  1. 2017Dialectometric analysis of language variation in Twittercited by 14
  2. 2019Modeling Global Syntactic Variation in English Using Dialect Classificationcited by 13
  3. 2013Where in the World are You? Geolocation and Language Identification in Twittercited by 11
  4. 2019Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammarcited by 11
  5. 2019Modeling the Complexity and Descriptive Adequacy of Construction Grammarscited by 9
  6. 2020Mapping Languages and Demographics with Georeferenced Corporacited by 6
  7. 2013Using Robust PCA to estimate regional characteristics of language use from geo-tagged Twitter messagescited by 2

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Cited by year

Citing papers per year: 2021: 2; 2022: 3; 2023: 3; 2024: 2; 2025: 1.

11 papers.