  Online Social Networks (OSNs) have come to play an increasingly important
role in our social lives, and their inherent privacy problems have become a
major concern for users. Can we assist consumers in their privacy
decision-making practices, for example by predicting their preferences and
giving them personalized advice? To this end, we introduce PPM: a Privacy
Prediction Model, rooted in psychological principles, which can be used to give
users personalized advice regarding their privacy decision-making practices.
Using this model, we study psychological variables that are known to affect
users' disclosure behavior: the trustworthiness of the requester/information
audience, the sharing tendency of the receiver/information holder, the
sensitivity of the requested/shared information, the appropriateness of the
request/sharing activities, as well as several more traditional contextual
factors.

Social and Information Networks;Computers and Society