Improving Readability Of Online Privacy Policies Through DOOP: A Domain Ontology For Online Privacy

Tracking #: 1846-3059

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Dhiren Audich
Rozita Dara
Blair Nonnecke

Responsible editor: 
Axel Polleres

Submission type: 
Full Paper
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 is proposed that reduces the amount of text a user has to read. It does so by 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. By using the ontology to locate key parts of privacy policies, average reading times were substantially reduced from 8 - 12 minutes to 45 seconds
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