Along with the growth of mobile and online social networks, internet users can exchange information easily. In order to match, the user must reveal his/her personal interests and information to recognize common cases among them. In some cases, users don't like to reveal all of their interests and personal information to others. They only want to fully reveal their interests if they are sure that there is a common interest between them and the intended user. Maintaining the privacy is one of the basic needs of each person in everyday life, that's why it has become one of the most important concerns of people in the virtual world. The purpose of this study was Maintaining the privacy of users in sharing and adjusting interests in Instagram. This study is looking for suitable methods for sharing and adjusting interests in Instagram with high security and convenient availability of information for the user which is evaluated by MANTHK method and is compared with aggressive background knowledge. In comparison of this method with other methods on MicroFTV dataset, regardless of the level of user privacy, the proposed method preserves the structural features of the network, better. However, all of the methods provide privacy for nodes in one level. Afterwards at the end of the research the proposed method is compared with a method without personalization and we have displayed that if every user has Safety sharing based on the needs of privacy, then efficiency of data can be increased.

privacy sharing adjusting the interests Instagram social networks.