Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling

Yan Shvartzshanider, Ananth Balashankar, Thomas Wies, Lakshminarayanan Subramanian


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.
Anthology ID:
2023.nllp-1.10
Original:
2023.nllp-1.10v1
Version 2:
2023.nllp-1.10v2
Volume:
Proceedings of the Natural Legal Language Processing Workshop 2023
Month:
December
Year:
2023
Address:
Singapore
Editors:
Daniel Preoțiuc-Pietro, Catalina Goanta, Ilias Chalkidis, Leslie Barrett, Gerasimos Spanakis, Nikolaos Aletras
Venues:
NLLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
85–98
Language:
URL:
https://aclanthology.org/2023.nllp-1.10
DOI:
Bibkey:
Cite (ACL):
Yan Shvartzshanider, Ananth Balashankar, Thomas Wies, and Lakshminarayanan Subramanian. 2023. Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling. In Proceedings of the Natural Legal Language Processing Workshop 2023, pages 85–98, Singapore. Association for Computational Linguistics.
Cite (Informal):
Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling (Shvartzshanider et al., NLLP-WS 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.nllp-1.10.pdf