Abstract: A system and method for predicting one or more sharing settings for a social network user is provided. The relevant user data is received and analyzed. Based on the analysis of the relevant user data, one or more of the user's desired sharing settings is predicted. In some embodiments, statistical analysis is used to analyze and/or predict the user's desired sharing settings. One or more predictions including a suggested sharing setting are generated. In one embodiment, the user's sharing settings are automatically adjusted based on the one or more predictions. In one embodiment, the one or more predictions are sent for display to the user. In one embodiment, feedback is obtained from the user accepting or rejecting the predictions. In one embodiment, the feedback is used to adjust one or more of the algorithms for analyzing the user data, predicting the user's desired sharing settings, or both.

Abstract: A system and method for adjusting privacy protection for a user in a plurality of applications is disclosed. A privacy protection request is sent to a user device. In one embodiment, the request is displayed on user device in the form of a pop-up window. In another embodiment, the request is displayed in a privacy settings area. The privacy protection request includes a plurality of protection levels. Once a protection level is selected the protection level is sent back and received by the system. Privacy settings are adjusted according to the selected privacy protection level based on information stored in a master template. In some embodiments, the privacy protection level is translated to associated privacy settings. Once the privacy settings have been adjusted, the privacy settings are applied to a plurality of online applications associated with the user based on the privacy protection level selected.

Abstract: A system and method for generating privacy-enhanced aggregate statistics within a social network system is provided. Data is collected and processed to gather information to generate the aggregate statistics. A threshold is assigned. The threshold includes a criterion used in making a determination on what aggregate statistic will be generated. In some embodiments, the threshold is a numerical value. In some embodiments, the numerical value, or quantitative data is then translated into qualitative descriptors. In some embodiments, noise is then added to randomize the assigned threshold. In other embodiments, noise is added to the collected data. In some embodiments, checks to guard against attacks from adversarial users are performed. Examples of indications of adversarial behavior include, but are not limited to, manipulation of profiles, continuous manipulation of affinity groups, and manipulation of preferences for one or more users. The threshold is applied and aggregate statistics are generated.

Abstract: A system and method for adjusting privacy protection for a user in a plurality of applications is disclosed. A privacy protection request is sent to a user device. In one embodiment, the request is displayed on user device in the form of a pop-up window. In another embodiment, the request is displayed in a privacy settings area. The privacy protection request includes a plurality of protection levels. Once a protection level is selected the protection level is sent back and received by the system. Privacy settings are adjusted according to the selected privacy protection level based on information stored in a master template. In some embodiments, the privacy protection level is translated to associated privacy settings. Once the privacy settings have been adjusted, the privacy settings are applied to a plurality of online applications associated with the user based on the privacy protection level selected.