E-privacy in 2nd generation E-commerce: privacy preferences versus actual behavior
Proceedings of the 3rd ACM conference on Electronic Commerce
Power strips, prophylactics, and privacy, oh my!
SOUPS '06 Proceedings of the second symposium on Usable privacy and security
Development of measures of online privacy concern and protection for use on the Internet
Journal of the American Society for Information Science and Technology
Security user studies: methodologies and best practices
CHI '07 Extended Abstracts on Human Factors in Computing Systems
Measuring self-disclosure online: Blurring and non-response to sensitive items in web-based surveys
Computers in Human Behavior
A Framework for Computing the Privacy Scores of Users in Online Social Networks
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
I've got 99 problems, but vibration ain't one: a survey of smartphone users' concerns
Proceedings of the second ACM workshop on Security and privacy in smartphones and mobile devices
Proceedings of the 5th Annual ACM Web Science Conference
Taking data exposure into account: how does it affect the choice of sign-in accounts?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security
Your browsing behavior for a big mac: economics of personal information online
Proceedings of the 22nd international conference on World Wide Web
Evaluation of challenges in human subject studies "in-the-wild" using subjects' personal smartphones
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
The price is right?: economic value of location sharing
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Retrospective privacy: managing longitudinal privacy in online social networks
Proceedings of the Ninth Symposium on Usable Privacy and Security
Guide to measuring privacy concern: Review of survey and observational instruments
International Journal of Human-Computer Studies
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The strong emotional reaction elicited by privacy issues is well documented (e.g., [12, 8]). The emotional aspect of privacy makes it difficult to evaluate privacy concern, and directly asking about a privacy issue may result in an emotional reaction and a biased response. This effect may be partly responsible for the dramatic privacy concern ratings coming from recent surveys, ratings that often seem to be at odds with user behavior. In this paper we propose indirect techniques for measuring content privacy concerns through surveys, thus hopefully diminishing any emotional response. We present a design for indirect surveys and test the design's use as (1) a means to measure relative privacy concerns across content types, (2) a tool for predicting unwillingness to share content (a possible indicator of privacy concern), and (3) a gauge for two underlying dimensions of privacy - content importance and the willingness to share content. Our evaluation consists of 3 surveys, taken by 200 users each, in which privacy is never asked about directly, but privacy warnings are issued with increasing escalation in the instructions and individual question-wording. We demonstrate that this escalation results in statistically and practically significant differences in responses to individual questions. In addition, we compare results against a direct privacy survey and show that rankings of privacy concerns are increasingly preserved as privacy language increases in the indirect surveys, thus indicating our mapping of the indirect questions to privacy ratings is accurately reflecting privacy concerns.