Indirect Content Privacy Surveys: Measuring Privacy Without Asking About It
Symposium on Usable Privacy and Security (SOUPS), ACM SIGCHI (2011)
Alex Braunstein, Laura Granka, Jessica Staddon
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 emo- tional 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 instruc- tions and individual question-wording. We demonstrate that this escalation results in statistically and practically signif- icant 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 sur- veys, thus indicating our mapping of the indirect questions to privacy ratings is accurately reflecting privacy concerns.