This chapter discusses authorship investigation studies, such as author verification, author attribution and author profiling, by means of automatic procedures. These procedures generally consist of two stages. In the first, we extract large numbers of counts of linguistic constructs (‘features’). In the second, we compare these counts between samples. On the basis of this comparison, we attempt to answer the authorship questions at hand. We describe various types of features and comparison methods, and the methodology to use them for studies. Then we present a case study, demonstrating that author verification with very high-quality results is possible, at least for book-length same-genre texts. Furthermore, we show that quality improves if rare features are included in the comparison data and that end-to-end deep learning systems already show high quality, but not yet at the level attained by traditional methods.
© 2001-2024 Fundación Dialnet · Todos los derechos reservados