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        <title>Finding Common Patterns in Domestic Violence Stories Posted on Reddit</title>
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            <namePart type="given">Mohit</namePart>
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    <abstract>Domestic violence survivors often share their experiences in online spaces, offering valuable insights into common abuse patterns. This study analyzes a dataset of personal narratives about domestic violence from Reddit, focusing on event extraction and topic modeling to uncover recurring themes. We evaluate GPT-4 and LLaMA-3.1 for extracting key sentences, finding that GPT-4 exhibits higher precision, while LLaMA-3.1 achieves better recall. Using LLM-based topic assignment, we identify dominant themes such as psychological aggression, financial abuse, and physical assault which align with previously published psychology findings. A co-occurrence and PMI analysis further reveals the interdependencies among different abuse types, emphasizing the multifaceted nature of domestic violence. Our findings provide a structured approach to analyzing survivor narratives, with implications for social support systems and policy interventions.</abstract>
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    <identifier type="doi">10.18653/v1/2025.wnu-1.6</identifier>
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        <date>2025-05</date>
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%0 Conference Proceedings
%T Finding Common Patterns in Domestic Violence Stories Posted on Reddit
%A Shokri, Mohammad
%A Klapper, Emily
%A Shan, Jason
%A Levitan, Sarah Ita
%Y Clark, Elizabeth
%Y Lal, Yash Kumar
%Y Chaturvedi, Snigdha
%Y Iyyer, Mohit
%Y Brei, Anneliese
%Y Modi, Ashutosh
%Y Chandu, Khyathi Raghavi
%S Proceedings of the The 7th Workshop on Narrative Understanding
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-247-3
%F shokri-etal-2025-finding
%X Domestic violence survivors often share their experiences in online spaces, offering valuable insights into common abuse patterns. This study analyzes a dataset of personal narratives about domestic violence from Reddit, focusing on event extraction and topic modeling to uncover recurring themes. We evaluate GPT-4 and LLaMA-3.1 for extracting key sentences, finding that GPT-4 exhibits higher precision, while LLaMA-3.1 achieves better recall. Using LLM-based topic assignment, we identify dominant themes such as psychological aggression, financial abuse, and physical assault which align with previously published psychology findings. A co-occurrence and PMI analysis further reveals the interdependencies among different abuse types, emphasizing the multifaceted nature of domestic violence. Our findings provide a structured approach to analyzing survivor narratives, with implications for social support systems and policy interventions.
%R 10.18653/v1/2025.wnu-1.6
%U https://aclanthology.org/2025.wnu-1.6/
%U https://doi.org/10.18653/v1/2025.wnu-1.6
%P 15-25

Markdown (Informal)

[Finding Common Patterns in Domestic Violence Stories Posted on Reddit](https://aclanthology.org/2025.wnu-1.6/) (Shokri et al., WNU 2025)

• Finding Common Patterns in Domestic Violence Stories Posted on Reddit (Shokri et al., WNU 2025)

ACL

• Mohammad Shokri, Emily Klapper, Jason Shan, and Sarah Ita Levitan. 2025. Finding Common Patterns in Domestic Violence Stories Posted on Reddit. In Proceedings of the The 7th Workshop on Narrative Understanding, pages 15–25, Albuquerque, New Mexico. Association for Computational Linguistics.