The Ph.D. thesis of Aigul Kaskina presents a privacy profile framework designed for the platform for political participation that allows to measure citizens’ privacy preferences and that models their privacy profiles using fuzzy clustering techniques. By applying fuzzy c-means and partitioning around medoids algorithms, fuzzy privacy profiles are used in the privacy settings recommender system’s architecture. Additionally, two user-centric evaluations were performed to estimate people’s perceptions of privacy settings recommendations. The initial results demonstrated that the adoption of the privacy settings recommendations depends on the citizens’ characteristics, here indicating inconsistent privacy behavior.