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it - Information Technology

Methods and Applications of Informatics and Information Technology

Editor-in-Chief: Conrad, Stefan / Molitor, Paul

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2196-7032
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Volume 58, Issue 5

Issues

Crowdsourcing privacy policy analysis: Potential, challenges and best practices

Florian Schaub
  • Corresponding author
  • Carnegie Mellon University, School of Computer Science, Pittsburgh, PA 15213, USA United States of America
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/ Travis D. Breaux / Norman Sadeh
Published Online: 2016-06-24 | DOI: https://doi.org/10.1515/itit-2016-0009

Abstract

Privacy policies are supposed to provide transparency about a service's data practices and help consumers make informed choices about which services to entrust with their personal information. In practice, those privacy policies are typically long and complex documents that are largely ignored by consumers. Even for regulators and data protection authorities privacy policies are difficult to assess at scale. Crowdsourcing offers the potential to scale the analysis of privacy policies with microtasks, for instance by assessing how specific data practices are addressed in privacy policies or extracting information about data practices of interest, which can then facilitate further analysis or be provided to users in more effective notice formats. Crowdsourcing the analysis of complex privacy policy documents to non-expert crowdworkers poses particular challenges. We discuss best practices, lessons learned and research challenges for crowdsourcing privacy policy analysis.

Keywords: Crowdsourcing; human-computer interaction; privacy; privacy policies; usability

ACM CCS: Information systems →World Wide Web →Web applications →Crowdsourcing; Security and privacy →Human and societal aspects of security and privacy →Privacy protections; Security and privacy →Human and societal aspects of security and privacy →Usability in security and privacy; Social and professional topics →Computing/technology policy →Privacy policies; Applied computing →Law; social and behavorial sciences →Law

About the article

Florian Schaub

Dr. Florian Schaub is a postdoctoral fellow in the School of Computer Science at Carnegie Mellon University. His research focuses on empowering users to effectively manage their privacy in complex socio-technological systems. His research interests span privacy, human-computer interaction, mobile and ubiquitous computing, and the Internet of Things. He received his Doctorate and Diplom in Computer Science from the University of Ulm, Germany, and a Bachelor in Information Technology from Deakin University, Australia.

Carnegie Mellon University, School of Computer Science, Pittsburgh, PA 15213, USA

Travis D. Breaux

Dr. Travis D. Breaux is an Assistant Professor appointed to the Institute for Software Research at Carnegie Mellon University. Dr. Breaux's research program searches for new methods and tools for developing correct software specifications and ensuring that software systems conform to those specifications in a transparent, reliable and trustworthy manner. His research on privacy and security has been recognized by the NSF Early CAREER award and best paper nominations from the IEEE International Requirements Engineering Conference. Dr. Breaux is a Senior member of the ACM SIGSOFT and IEEE Computer Society, he served as Chair of the USACM Privacy and Security Committee and on the USACM Executive Council.

Carnegie Mellon University, School of Computer Science, Pittsburgh, PA 15213, USA

Norman Sadeh

Dr. Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University, where he leads the Usable Privacy Policy Project, currently one of the largest privacy research projects in the United States. He also directs the Mobile Commerce Lab and co-directs the School's Master's Program in Privacy Engineering. He received his PhD in Computer Science at Carnegie Mellon University with a Major in Artificial Intelligence.

Carnegie Mellon University, School of Computer Science, Pittsburgh, PA 15213, USA


Accepted: 2016-05-24

Received: 2016-02-17

Published Online: 2016-06-24

Published in Print: 2016-10-28


Citation Information: it - Information Technology, Volume 58, Issue 5, Pages 229–236, ISSN (Online) 2196-7032, ISSN (Print) 1611-2776, DOI: https://doi.org/10.1515/itit-2016-0009.

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