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Modeling Global Syntactic Variation in English Using Dialect Classification

arXiv 1904.05527 ↗First posted 11 Apr 2019cs.CLcited by 13

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Abstract (arXiv)

This paper evaluates global-scale dialect identification for 14 national varieties of English as a means for studying syntactic variation. The paper makes three main contributions: (i) introducing data-driven language mapping as a method for selecting the inventory of national varieties to include in the task; (ii) producing a large and dynamic set of syntactic features using grammar induction rather than focusing on a few hand-selected features such as function words; and (iii) comparing models across both web corpora and social media corpora in order to measure the robustness of syntactic variation across registers.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Apr 2019.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 3; 2024: 2.

13 papers.

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  1. 2024Natural Language Processing for Dialects of a Language: A Surveycited by 40
  2. 2022Geographic Adaptation of Pretrained Language Modelscited by 14
  3. 2021Global Syntactic Variation in Seven Languages: Towards a Computational Dialectologycited by 11
  4. 2021Representations of Language Varieties Are Reliable Given Corpus Similarity Measurescited by 10
  5. 2021Production vs Perception: The Role of Individuality in Usage-Based Grammar Inductioncited by 6
  6. 2021Learned Construction Grammars Converge Across Registers Given Increased Exposurecited by 6
  7. 2022Exposure and Emergence in Usage-Based Grammar: Computational Experiments in 35 Languagescited by 6
  8. 2022Stability of Syntactic Dialect Classification Over Space and Timecited by 5
  9. 2023Exploring the Constructicon: Linguistic Analysis of a Computational CxGcited by 3
  10. 2023Variation and Instability in Dialect-Based Embedding Spacescited by 3
  11. 2023Syntactic Variation Across the Grammar: Modelling a Complex Adaptive Systemcited by 1
  12. 2021Measuring Linguistic Diversity During COVID-19cited by 0
1 more
  1. 2024Validating and Exploring Large Geographic Corporacited by 0