Crowdsourcing annotations for websites' privacy policies: Can it really work?

Shomir Wilson, Florian Schaub, Rohan Ramanath, Norman Sadeh, Fei Liu, Noah A. Smith, Frederick Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

Website privacy policies are often long and difficult to understand. While research shows that Internet users care about their privacy, they do not have time to understand the policies of every website they visit, and most users hardly ever read privacy policies. Several recent efforts aim to crowdsource the interpretation of privacy policies and use the resulting annotations to build more effective user interfaces that provide users with salient policy summaries. However, very little attention has been devoted to studying the accuracy and scalability of crowdsourced privacy policy annotations, the types of questions crowdworkers can effectively answer, and the ways in which their productivity can be enhanced. Prior research indicates that most Internet users often have great difficulty understanding privacy policies, suggesting limits to the effectiveness of crowdsourcing approaches. In this paper, we assess the viability of crowdsourcing privacy policy annotations. Our results suggest that, if carefully deployed, crowdsourcing can indeed result in the generation of non-Trivial annotations and can also help identify elements of ambiguity in policies. We further introduce and evaluate a method to improve the annotation process by predicting and highlighting paragraphs relevant to specific data practices.

Original languageEnglish (US)
Title of host publication25th International World Wide Web Conference, WWW 2016
PublisherInternational World Wide Web Conferences Steering Committee
Pages133-143
Number of pages11
ISBN (Electronic)9781450341431
DOIs
StatePublished - Jan 1 2016
Event25th International World Wide Web Conference, WWW 2016 - Montreal, Canada
Duration: Apr 11 2016Apr 15 2016

Publication series

Name25th International World Wide Web Conference, WWW 2016

Other

Other25th International World Wide Web Conference, WWW 2016
CountryCanada
CityMontreal
Period4/11/164/15/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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  • Cite this

    Wilson, S., Schaub, F., Ramanath, R., Sadeh, N., Liu, F., Smith, N. A., & Liu, F. (2016). Crowdsourcing annotations for websites' privacy policies: Can it really work? In 25th International World Wide Web Conference, WWW 2016 (pp. 133-143). (25th International World Wide Web Conference, WWW 2016). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/2872427.2883035