@inproceedings{shvartzshanider-etal-2023-beyond,
title = "Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling",
author = "Shvartzshanider, Yan and
Balashankar, Ananth and
Wies, Thomas and
Subramanian, Lakshminarayanan",
editor = "Preo{\textcommabelow{t}}iuc-Pietro, Daniel and
Goanta, Catalina and
Chalkidis, Ilias and
Barrett, Leslie and
Spanakis, Gerasimos (Jerry) and
Aletras, Nikolaos",
booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2023",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.nllp-1.10",
pages = "85--98",
abstract = "This paper formulates a new task of extracting privacy parameters from a privacy policy, through the lens of Contextual Integrity (CI), an established social theory framework for reasoning about privacy norms. Through extensive experiments, we further show that incorporating CI-based domain-specific knowledge into a BERT-based SRL model results in the highest precision and recall, achieving an F1 score of 84{\%}. With our work, we would like to motivate new research in building NLP applications for the privacy domain.",
}
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<abstract>This paper formulates a new task of extracting privacy parameters from a privacy policy, through the lens of Contextual Integrity (CI), an established social theory framework for reasoning about privacy norms. Through extensive experiments, we further show that incorporating CI-based domain-specific knowledge into a BERT-based SRL model results in the highest precision and recall, achieving an F1 score of 84%. With our work, we would like to motivate new research in building NLP applications for the privacy domain.</abstract>
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%0 Conference Proceedings
%T Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling
%A Shvartzshanider, Yan
%A Balashankar, Ananth
%A Wies, Thomas
%A Subramanian, Lakshminarayanan
%Y Preo\textcommabelowtiuc-Pietro, Daniel
%Y Goanta, Catalina
%Y Chalkidis, Ilias
%Y Barrett, Leslie
%Y Spanakis, Gerasimos (Jerry)
%Y Aletras, Nikolaos
%S Proceedings of the Natural Legal Language Processing Workshop 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F shvartzshanider-etal-2023-beyond
%X This paper formulates a new task of extracting privacy parameters from a privacy policy, through the lens of Contextual Integrity (CI), an established social theory framework for reasoning about privacy norms. Through extensive experiments, we further show that incorporating CI-based domain-specific knowledge into a BERT-based SRL model results in the highest precision and recall, achieving an F1 score of 84%. With our work, we would like to motivate new research in building NLP applications for the privacy domain.
%U https://aclanthology.org/2023.nllp-1.10
%P 85-98
Markdown (Informal)
[Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling](https://aclanthology.org/2023.nllp-1.10) (Shvartzshanider et al., NLLP-WS 2023)
ACL