Designing Natural Language and Structured Entry Methods for Privacy Policy Authoring

Human-Computer Interaction - INTERACT 2005 - Lecture Notes in Computer Science ◽

10.1007/11555261_54 ◽

2005 ◽

pp. 671-684 ◽

Cited By ~ 12

Author(s):

John Karat ◽

Clare-Marie Karat ◽

Carolyn Brodie ◽

Jinjuan Feng

Keyword(s):

Natural Language ◽

Download Full-text

An empirical study of natural language parsing of privacy policy rules using the SPARCLE policy workbench

Proceedings of the second symposium on Usable privacy and security - SOUPS '06 ◽

10.1145/1143120.1143123 ◽

2006 ◽

Cited By ~ 60

Author(s):

Carolyn A. Brodie ◽

Clare-Marie Karat ◽

John Karat

Keyword(s):

Empirical Study ◽

Natural Language ◽

Policy Rules ◽

Natural Language Parsing

Download Full-text

Improving Readability of Online Privacy Policies through DOOP: A Domain Ontology for Online Privacy

Digital ◽

10.3390/digital1040015 ◽

2021 ◽

Vol 1 (4) ◽

pp. 198-215

Author(s):

Dhiren A. Audich ◽

Rozita Dara ◽

Blair Nonnecke

Keyword(s):

Natural Language Processing ◽

Natural Language ◽

Language Processing ◽

Domain Ontology ◽

Online Privacy ◽

Proof Of Concept ◽

Privacy Policies ◽

Privacy Concerns ◽

Novel Approach

Privacy policies play an important part in informing users about their privacy concerns by operating as memorandums of understanding (MOUs) between them and online services providers. Research suggests that these policies are infrequently read because they are often lengthy, written in jargon, and incomplete, making them difficult for most users to understand. Users are more likely to read short excerpts of privacy policies if they pertain directly to their concern. In this paper, a novel approach and a proof-of-concept tool are proposed that reduces the amount of privacy policy text a user has to read. It does so using a domain ontology and natural language processing (NLP) to identify key areas of the policies that users should read to address their concerns and take appropriate action. Using the ontology to locate key parts of privacy policies, average reading times were substantially reduced from 29 to 32 min to 45 s.

Download Full-text