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Automated Detection and Analysis of Data Practices Using A Real-World Corpus
Feb. 20, 2024, 5:43 a.m. | Mukund Srinath, Pranav Venkit, Maria Badillo, Florian Schaub, C. Lee Giles, Shomir Wilson
cs.LG updates on arXiv.org arxiv.org
Abstract: Privacy policies are crucial for informing users about data practices, yet their length and complexity often deter users from reading them. In this paper, we propose an automated approach to identify and visualize data practices within privacy policies at different levels of detail. Leveraging crowd-sourced annotations from the ToS;DR platform, we experiment with various methods to match policy excerpts with predefined data practice descriptions. We further conduct a case study to evaluate our approach on …
abstract analysis and analysis arxiv automated complexity cs.cr cs.lg data detection identify paper practices privacy privacy policies reading them type world
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