A Survey on Stylometric Text Features

Lagutina, Ksenia; Lagutina, Nadezhda; Boychuk, Elena; Vorontsova, Inna; Shliakhtina, Elena; Belyaeva, Olga; Paramonov, Ilya; Demidov, P.G.

doi:10.23919/fruct48121.2019.8981504

Cited by 63Authorship Attribution and ProfilingNatural Language Processing TechniquesDiscourse Analysis in Language Studies

A Survey on Stylometric Text Features

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Lagutina, Ksenia, Lagutina, Nadezhda, Boychuk, Elena, Vorontsova, Inna, Shliakhtina, Elena, Belyaeva, Olga, Paramonov, Ilya, Demidov, P.G.·2019·2019 25th Conference of Open Innovations Association (FRUCT)

DOI 10.23919/fruct48121.2019.8981504

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Abstract

Ways of individual style expression in a natural language include amongst other things stylometric features. These can be automatically detected with the use of computational linguistics methods. In this survey we systematize the recent studies devoted to extraction and application of stylometric features in solving natural language processing tasks: authorship attribution, authorship verification, style change detection, authorship profiling, and text classification by genre and sentiment. For that purpose we define stylometric feature categories that provide for the most effective solutions, discuss reasons for their successful application, touch upon the limitations of approaches based on their application, and make suggestions for future research.

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Authors: Lagutina, K., Lagutina, N., Boychuk, E., Vorontsova, I., Shliakhtina, E., Belyaeva, O., Paramonov, I., & Demidov, P. G.
Affiliations: Yaroslavl State University (RU)
Yaroslavl State Pedagogical University (RU)
ORCID: Lagutina, Ksenia
Lagutina, Nadezhda
Boychuk, Elena
Vorontsova, Inna
Shliakhtina, Elena
Paramonov, Ilya
Demidov, P.G.
Venue: 2019 25th Conference of Open Innovations Association (FRUCT)
Publisher: IEEE
Published: 2019-11
Pages: 184-195
DOI: 10.23919/fruct48121.2019.8981504
OpenAlex: W3004919414
Cited by: 63
References: 53
Citations by year: 2026: 3 · 2025: 8 · 2024: 10 · 2023: 14 · 2022: 12 · 2021: 12 · 2020: 4
FWCI: 2.68
Type: conference paper
Language: en
Open access: green
doaj.org
Licence: cc-by-sa
Locations: Conference of Open Innovations Association (FRUCT) (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Authorship Attribution and Profiling
Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
Social Sciences › Arts and Humanities › Literature and Literary Theory › Discourse Analysis in Language Studies
Keywords: stylometry, stylometric features, authorship attribution, authorship verification, genre classification, sentiment analysis, text classification, feature extraction

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A Survey on Stylometric Text Features

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