@inproceedings{ifergan-etal-2024-identifying,
title = "Identifying Narrative Patterns and Outliers in Holocaust Testimonies Using Topic Modeling",
author = "Ifergan, Maxim and
Abend, Omri and
Keydar, Renana and
Pinchevski, Amit",
editor = "Anuradha, Isuri and
Wynne, Martin and
Frontini, Francesca and
Plum, Alistair",
booktitle = "Proceedings of the First Workshop on Holocaust Testimonies as Language Resources (HTRes) @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.htres-1.7",
pages = "44--52",
abstract = "The vast collection of Holocaust survivor testimonies presents invaluable historical insights but poses challenges for manual analysis. This paper leverages advanced Natural Language Processing (NLP) techniques to explore the USC Shoah Foundation Holocaust testimony corpus. By treating testimonies as structured question-and-answer sections, we apply topic modeling to identify key themes. We experiment with BERTopic, which leverages recent advances in language modeling technology. We align testimony sections into fixed parts, revealing the evolution of topics across the corpus of testimonies. This highlights both a common narrative schema and divergences between subgroups based on age and gender. We introduce a novel method to identify testimonies within groups that exhibit atypical topic distributions resembling those of other groups. This study offers unique insights into the complex narratives of Holocaust survivors, demonstrating the power of NLP to illuminate historical discourse and identify potential deviations in survivor experiences.",
}
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<abstract>The vast collection of Holocaust survivor testimonies presents invaluable historical insights but poses challenges for manual analysis. This paper leverages advanced Natural Language Processing (NLP) techniques to explore the USC Shoah Foundation Holocaust testimony corpus. By treating testimonies as structured question-and-answer sections, we apply topic modeling to identify key themes. We experiment with BERTopic, which leverages recent advances in language modeling technology. We align testimony sections into fixed parts, revealing the evolution of topics across the corpus of testimonies. This highlights both a common narrative schema and divergences between subgroups based on age and gender. We introduce a novel method to identify testimonies within groups that exhibit atypical topic distributions resembling those of other groups. This study offers unique insights into the complex narratives of Holocaust survivors, demonstrating the power of NLP to illuminate historical discourse and identify potential deviations in survivor experiences.</abstract>
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%0 Conference Proceedings
%T Identifying Narrative Patterns and Outliers in Holocaust Testimonies Using Topic Modeling
%A Ifergan, Maxim
%A Abend, Omri
%A Keydar, Renana
%A Pinchevski, Amit
%Y Anuradha, Isuri
%Y Wynne, Martin
%Y Frontini, Francesca
%Y Plum, Alistair
%S Proceedings of the First Workshop on Holocaust Testimonies as Language Resources (HTRes) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F ifergan-etal-2024-identifying
%X The vast collection of Holocaust survivor testimonies presents invaluable historical insights but poses challenges for manual analysis. This paper leverages advanced Natural Language Processing (NLP) techniques to explore the USC Shoah Foundation Holocaust testimony corpus. By treating testimonies as structured question-and-answer sections, we apply topic modeling to identify key themes. We experiment with BERTopic, which leverages recent advances in language modeling technology. We align testimony sections into fixed parts, revealing the evolution of topics across the corpus of testimonies. This highlights both a common narrative schema and divergences between subgroups based on age and gender. We introduce a novel method to identify testimonies within groups that exhibit atypical topic distributions resembling those of other groups. This study offers unique insights into the complex narratives of Holocaust survivors, demonstrating the power of NLP to illuminate historical discourse and identify potential deviations in survivor experiences.
%U https://aclanthology.org/2024.htres-1.7
%P 44-52
Markdown (Informal)
[Identifying Narrative Patterns and Outliers in Holocaust Testimonies Using Topic Modeling](https://aclanthology.org/2024.htres-1.7) (Ifergan et al., htres-WS 2024)
ACL