Moving from the assumption that formal, rather than content features, can be used to detect differences and similarities among textual genres and registers, this paper presents a new approach to linguistic profiling - a well-established methodological framework to study language variation - which is applied to detect significant variations within the internal structure of a text. We test this approach on the Italian language using a wide spectrum of linguistic features automatically extracted from parsed corpora representative of four main genres and two levels of complexity for each, and we show that it is possible to model the degree of stylistic variance within texts according to genre and language complexity

Lost in Text: A Cross-Genre Analysis of Linguistic Phenomena within Text

Dominique Brunato;Felice Dell'Orletta
2020

Abstract

Moving from the assumption that formal, rather than content features, can be used to detect differences and similarities among textual genres and registers, this paper presents a new approach to linguistic profiling - a well-established methodological framework to study language variation - which is applied to detect significant variations within the internal structure of a text. We test this approach on the Italian language using a wide spectrum of linguistic features automatically extracted from parsed corpora representative of four main genres and two levels of complexity for each, and we show that it is possible to model the degree of stylistic variance within texts according to genre and language complexity
2020
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
natural language processing
computational stylometry
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/401391
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact