Semi-Automated Analysis of Large Privacy Policy Corpora

dc.contributor.author Dima, Alden
dc.contributor.author Massey, Aaron
dc.date.accessioned 2020-12-24T19:57:57Z
dc.date.available 2020-12-24T19:57:57Z
dc.date.issued 2021-01-05
dc.description.abstract Regulators, policy makers, and consumers are interested in proactively identifying services with acceptable or compliant data use policies, privacy policies, and terms of service. Academic requirements engineering researchers and legal scholars have developed qualitative, manual approaches to conducting requirements analysis of policy documents to identify concerns and compare services against preferences or standards. In this research, we develop and present an approach to conducting large-scale, qualitative, prospective analyses of policy documents with respect to the wide-variety of normative concerns found in policy documents. Our approach uses techniques from natural language processing, including topic modeling and summarization. We evaluate our approach in an exploratory case study that attempts to replicate a manual legal analysis of roughly 200 privacy policies from seven domains in a semi-automated fashion at a larger scale. Our findings suggest that this approach is promising for some concerns.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2021.563
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/71180
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Privacy and Economics
dc.subject natural language processing
dc.subject privacy policy analysis.
dc.subject requirements analysis
dc.title Semi-Automated Analysis of Large Privacy Policy Corpora
prism.startingpage 4641
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