  This paper develops a construction-based dialectometry capable of identifying
previously unknown constructions and measuring the degree to which a given
construction is subject to regional variation. The central idea is to learn a
grammar of constructions (a CxG) using construction grammar induction and then
to use these constructions as features for dialectometry. This offers a method
for measuring the aggregate similarity between regional CxGs without limiting
in advance the set of constructions subject to variation. The learned CxG is
evaluated on how well it describes held-out test corpora while dialectometry is
evaluated on how well it can model regional varieties of English. Themethod is
tested using two distinct datasets: First, the International Corpus of English
representing eight outer circle varieties; Second, a web-crawled corpus
representing five inner circle varieties. Results show that themethod (1)
produces a grammar with stable quality across sub-sets of a single corpus that
is (2) capable of distinguishing between regional varieties of Englishwith a
high degree of accuracy, thus (3) supporting dialectometricmethods formeasuring
the similarity between varieties of English and (4) measuring the degree to
which each construction is subject to regional variation. This is important for
cognitive sociolinguistics because it operationalizes the idea that competition
between constructions is organized at the functional level so that
dialectometry needs to represent as much of the available functional space as
possible.
