We investigate authorship attribution using
classifiers based on frame semantics. The purpose
is to discover whether adding semantic
information to lexical and syntactic methods
for authorship attribution will improve them,
specifically to address the difficult problem of
authorship attribution of translated texts. Our
results suggest (i) that frame-based classifiers
are usable for author attribution of both translated
and untranslated texts; (ii) that framebased
classifiers generally perform worse than
the baseline classifiers for untranslated texts,
but (iii) perform as well as, or superior to
the baseline classifiers on translated texts; (iv)
that—contrary to current belief—naïve classifiers
based on lexical markers may perform
tolerably on translated texts if the combination
of author and translator is present in the training
set of a classifier.