Contextual Integrity has been proposed to define privacy in an unusual way. Most approaches take into account a sensitivity level or a ``privacy circle'': the information is said to be either private or public and to be constrained to a given group of agents, \textit{e.g.} ``my friends'', when private. In the opposite, Contextual Integrity states that any information transmitted can make this transmission a privacy violation depending on its context. In this thesis, we use this theory to develop a novel model that one can use in an open and decentralized virtual community to socially enforce privacy. This thesis defines the PrivaCIAS model, in which privacy constraints are formally described to be used to detect privacy violations according to the Contextual Integrity theory. The PrivaCIAS model provides norms to agents in order to make them implement social control. The model does not require a central authority, it gives control to the agents for detecting privacy violations (through Contextual Integrity) and excluding violating agents from the system through social exclusion. This model targets decentralized social networks as a main application domain.