Abstract
Most of the work on Character Networks to date is limited to monolingual texts. Conversely, in this paper we apply and analyze Character Networks on both source texts (English novels) and their Finnish translations (both human- and machine-translated). We assume that this analysis could provide some insights on changes in translations that could modify the character networks, as well as the narrative. The results show that the character networks of translations differ from originals in case of long novels, and the differences may also vary depending on the novel and translator’s strategy.- Anthology ID:
- 2022.latechclfl-1.10
- Volume:
- Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Stefania Degaetano, Anna Kazantseva, Nils Reiter, Stan Szpakowicz
- Venue:
- LaTeCHCLfL
- SIG:
- SIGHUM
- Publisher:
- International Conference on Computational Linguistics
- Note:
- Pages:
- 75–82
- Language:
- URL:
- https://aclanthology.org/2022.latechclfl-1.10
- DOI:
- Cite (ACL):
- Aleksandra Konovalova and Antonio Toral. 2022. Man vs. Machine: Extracting Character Networks from Human and Machine Translations. In Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 75–82, Gyeongju, Republic of Korea. International Conference on Computational Linguistics.
- Cite (Informal):
- Man vs. Machine: Extracting Character Networks from Human and Machine Translations (Konovalova & Toral, LaTeCHCLfL 2022)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/2022.latechclfl-1.10.pdf