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
