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| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.ancejournal | IJCOL | - |
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Chiara Buongiovann | it |
| dc.authority.people | Francesco Gracci | it |
| dc.authority.people | Dominique Brunato | it |
| dc.authority.people | Felice Dell'Orletta | it |
| dc.collection.id.s | b3f88f24-048a-4e43-8ab1-6697b90e068e | * |
| dc.collection.name | 01.01 Articolo in rivista | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/21 05:20:35 | - |
| dc.date.available | 2024/02/21 05:20:35 | - |
| dc.date.issued | 2020 | - |
| dc.description.abstracteng | 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 | - |
| dc.description.affiliations | Università di Pisa; Università di Pisa; Istituto di Linguistica Computazionale"Antonio Zampolli" (ILC-CNR); Istituto di Linguistica Computazionale"Antonio Zampolli" (ILC-CNR) | - |
| dc.description.allpeople | Chiara Buongiovann; Francesco Gracci; Dominique Brunato; Felice Dell'Orletta | - |
| dc.description.allpeopleoriginal | Chiara Buongiovann, Francesco Gracci, Dominique Brunato, Felice Dell'Orletta | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 2 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/401391 | - |
| dc.identifier.url | https://www.ai-lc.it/wp-content/uploads/2021/03/IJCOL_6_1_3_buongiovanni_et_al.pdf | - |
| dc.language.iso | eng | - |
| dc.relation.issue | 1 | - |
| dc.relation.volume | 6 | - |
| dc.subject.keywords | natural language processing | - |
| dc.subject.keywords | computational stylometry | - |
| dc.subject.singlekeyword | natural language processing | * |
| dc.subject.singlekeyword | computational stylometry | * |
| dc.title | Lost in Text: A Cross-Genre Analysis of Linguistic Phenomena within Text | en |
| dc.type.driver | info:eu-repo/semantics/article | - |
| dc.type.full | 01 Contributo su Rivista::01.01 Articolo in rivista | it |
| dc.type.miur | 262 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 450804 | - |
| iris.orcid.lastModifiedDate | 2024/02/22 21:39:42 | * |
| iris.orcid.lastModifiedMillisecond | 1708634382403 | * |
| iris.scopus.extIssued | 2020 | - |
| iris.scopus.extTitle | Lost in Text: A Cross-Genre Analysis of Linguistic Phenomena within Text | - |
| iris.sitodocente.maxattempts | 3 | - |
| Appare nelle tipologie: | 01.01 Articolo in rivista | |
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