@inproceedings{shokri-etal-2024-safe,
    title = "Is It Safe to Tell Your Story? Towards Achieving Privacy for Sensitive Narratives",
    author = "Shokri, Mohammad  and
      Bishop, Allison  and
      Levitan, Sarah Ita",
    editor = "Lal, Yash Kumar  and
      Clark, Elizabeth  and
      Iyyer, Mohit  and
      Chaturvedi, Snigdha  and
      Brei, Anneliese  and
      Brahman, Faeze  and
      Chandu, Khyathi Raghavi",
    booktitle = "Proceedings of the 6th Workshop on Narrative Understanding",
    month = nov,
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.wnu-1.7/",
    doi = "10.18653/v1/2024.wnu-1.7",
    pages = "47--54",
    abstract = "Evolving tools for narrative analysis present an opportunity to identify common structure in stories that are socially important to tell, such as stories of survival from domestic abuse. A greater structural understanding of such stories could lead to stronger protections against de-anonymization, as well as future tools to help survivors navigate the complex trade-offs inherent in trying to tell their stories safely. In this work we explore narrative patterns within a small set of domestic violence stories, identifying many similarities. We then propose a method to assess the safety of sharing a story based on a distance feature vector."
}