Computational Analysis of Character Development in Holocaust Testimonies

Esther Shizgal, Eitan Wagner, Renana Keydar, Omri Abend


Abstract
This work presents a computational approach to analyze character development along the narrative timeline. The analysis characterizes changes in the protagonist’s views and behavior and the interplay between them. We consider transcripts of Holocaust survivor testimonies as a test case, each telling the story of an individual in first-person terms. We focus on the survivor’s religious trajectory, examining the evolution of their disposition toward religious belief and practice as it is reflected in the testimony. Clustering the resulting trajectories in the dataset, we identify common sequences in the data. Our findings highlight multiple common structures of religiosity across the narratives: in terms of belief, a constant disposition is common, while for practice, most present an oscillating structure, serving as valuable material for historical and sociological research. This work demonstrates the potential of natural language processing for analyzing character evolution through thematic trajectories in narratives.
Anthology ID:
2025.emnlp-main.1156
Volume:
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Christos Christodoulopoulos, Tanmoy Chakraborty, Carolyn Rose, Violet Peng
Venue:
EMNLP
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Publisher:
Association for Computational Linguistics
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Pages:
22721–22745
Language:
URL:
https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.1156/
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Bibkey:
Cite (ACL):
Esther Shizgal, Eitan Wagner, Renana Keydar, and Omri Abend. 2025. Computational Analysis of Character Development in Holocaust Testimonies. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 22721–22745, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
Computational Analysis of Character Development in Holocaust Testimonies (Shizgal et al., EMNLP 2025)
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https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.1156.pdf
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