A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Analyzing register variation in web texts through automatic segmentation
Tekijät: Henriksson, Erik; Hellström, Saara; Laippala, Veronika
Toimittaja: Hämäläinen, Mika; Öhman, Emily; Bizzoni, Yuri; Miyagawa, So; Alnajjar, Khalid
Konferenssin vakiintunut nimi: International Conference on Natural Language Processing for Digital Humanities
Julkaisuvuosi: 2025
Kokoomateoksen nimi: Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities
Aloitussivu: 7
Lopetussivu: 19
ISBN: 979-8-89176-234-3
DOI: https://doi.org/10.18653/v1/2025.nlp4dh-1.2
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Kokonaan avoin julkaisukanava
Verkko-osoite: https://doi.org/10.18653/v1/2025.nlp4dh-1.2
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/508751027
Rinnakkaistallenteen lisenssi: CC BY
Rinnakkaistallennetun julkaisun versio: Kustantajan versio
This study introduces a novel method for analyzing register variation in web texts through classification-based register segmentation. While traditional text-linguistic register analysis treats web documents as single units, we present a recursive binary segmentation approach that automatically identifies register shifts within web documents without labeled segment data, using a ModernBERT classifier fine-tuned on full web documents. Manual evaluation shows our approach to be reliable, and our experimental results reveal that register segmentation leads to more accurate register classification, helps models learn more distinct register categories, and produces text units with more consistent linguistic characteristics. The approach offers new insights into documentinternal register variation in online discourse.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
