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            <namePart type="given">Anna</namePart>
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    <abstract>Automated scene segmentation is an ongoing challenge in computational literary studies (CLS) to approach literary texts by analyzing comparable units. In this paper, we present our approach (work in progress) to text segmentation using a classifier that identifies the position of a scene change in English-language fiction. By manually annotating novels from a 20th-century US-English romance fiction corpus, we prepared training data for fine-tuning transformer models, yielding promising preliminary results for improving automated text segmentation in CLS.</abstract>
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%0 Conference Proceedings
%T Rethinking Scene Segmentation. Advancing Automated Detection of Scene Changes in Literary Texts
%A Guhr, Svenja
%A Mao, Huijun
%A Lin, Fengyi
%Y Kazantseva, Anna
%Y Szpakowicz, Stan
%Y Degaetano-Ortlieb, Stefania
%Y Bizzoni, Yuri
%Y Pagel, Janis
%S Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025)
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-241-1
%F guhr-etal-2025-rethinking
%X Automated scene segmentation is an ongoing challenge in computational literary studies (CLS) to approach literary texts by analyzing comparable units. In this paper, we present our approach (work in progress) to text segmentation using a classifier that identifies the position of a scene change in English-language fiction. By manually annotating novels from a 20th-century US-English romance fiction corpus, we prepared training data for fine-tuning transformer models, yielding promising preliminary results for improving automated text segmentation in CLS.
%R 10.18653/v1/2025.latechclfl-1.8
%U https://aclanthology.org/2025.latechclfl-1.8/
%U https://doi.org/10.18653/v1/2025.latechclfl-1.8
%P 79-86

Markdown (Informal)

[Rethinking Scene Segmentation. Advancing Automated Detection of Scene Changes in Literary Texts](https://aclanthology.org/2025.latechclfl-1.8/) (Guhr et al., LaTeCHCLfL 2025)

• Rethinking Scene Segmentation. Advancing Automated Detection of Scene Changes in Literary Texts (Guhr et al., LaTeCHCLfL 2025)

ACL

• Svenja Guhr, Huijun Mao, and Fengyi Lin. 2025. Rethinking Scene Segmentation. Advancing Automated Detection of Scene Changes in Literary Texts. In Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025), pages 79–86, Albuquerque, New Mexico. Association for Computational Linguistics.