Online Social Networks (OSNs) have come to play an increasingly importantrole in our social lives, and their inherent privacy problems have become amajor concern for users. Can we assist consumers in their privacydecision-making practices, for example by predicting their preferences andgiving them personalized advice? To this end, we introduce PPM: a PrivacyPrediction Model, rooted in psychological principles, which can be used to giveusers personalized advice regarding their privacy decision-making practices.Using this model, we study psychological variables that are known to affectusers' disclosure behavior: the trustworthiness of the requester/informationaudience, the sharing tendency of the receiver/information holder, thesensitivity of the requested/shared information, the appropriateness of therequest/sharing activities, as well as several more traditional contextualfactors.
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