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Although Online Social Network (OSN) services offer users a variety of benefits, they also bring new threats and privacy issues to the community. In this paper, we first define the data types in OSN services and the states of shared data with respect to Optimal, Under-shared, Over-shared, and Hybrid states. We also identify the facilitating, detracting, and preventive parameters that are responsible for the state transition of the data. We address that, in a reliable OSN service, a user should be able to set up his or her desired level of information sharing with a certain group of other users. However, it is not always clear to the ordinary users how to decide how much information they should reveal to others. Therefore, we propose an approach for helping OSN users determine their optimum levels of information sharing, taking into consideration the payoffs (potential Reward or Cost) based on the Markov decision process (MDP).