Improving the prediction of users’ disclosure behavior… by making them disclose more predictably?

Taking a step beyond segmentation, privacy researchers have recently proposed privacy personalization or adaptation as an approach to assist users in their privacy decision making. Analyzing a number of datasets of users’ personal information disclosure behavior, we find an interesting phenomenon regarding privacy personalization: the order in which information is requested has an impact on prediction accuracy. We provide
evidence that this happens because certain request orders cause people’s disclosure behavior to be less variable and thus more predictable. This is an important phenomenon to study, because if request orders indeed influence the variability and predictability of subsequent requests, then adapting the request order to the user may result in positive feedback loops that promote prediction accuracy. We address several possible explanations for this phenomenon, and we propose a study that will help us find out which of these explanations is correct.