Crowdsourcing the Extraction of Data Practices from Privacy Policies


  • Florian Schaub Carnegie Mellon University
  • Travis Breaux Carnegie Mellon University
  • Norman Sadeh Carnegie Mellon University



privacy, privacy policies, web privacy, crowdsourcing, extraction, data practices


Website and mobile application privacy policies are intended to describe the system’s data practices. However, they are often written in non-standard formats and contain ambiguities that make it difficult for users to read and comprehend these documents. We propose a crowdsourcing approach to extract data practices from privacy policies to provide more concise and useable privacy notices to users and support the analysis of stated data practices. To that end, we designed a hierarchical task workflow for crowdsourcing the extraction of data practices from privacy policies. We discuss our workflow design and report preliminary results.




How to Cite

Schaub, F., Breaux, T., & Sadeh, N. (2014). Crowdsourcing the Extraction of Data Practices from Privacy Policies. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1), 56-57.