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.
@article{arxiv.1904.05527,
title = {Modeling Global Syntactic Variation in English Using Dialect Classification},
author = {Jonathan Dunn},
journal= {arXiv preprint arXiv:1904.05527},
year = {2019}
}