The main goal of this work is to facilitate the exchange of information among the members of the social network by extending the functionality of the social network. The network should have the functionality that could provide not only the most relevant information to the particular member of the network but also with some additional information that could be of some interest to that member (user of the system). Such functionality can be achieved by extending social network with recommendation management subsystem. In this work, recommendation is defined as an informal or formal statement defining what information should be provided to the particular user. This work covers the method of the formation of personalized recommendations. The formation of them is based on leverage coefficients. This way of formation of recommendations allows defining the most suitable level of flexibility and personalization. This provides selection and presentation of proper additional information. The algorithm of formation of recommendations, described is this work, formally defines the composition of recommendation. Recommendation is saved as substantive element of the social network. It consist of finite set of atomic elements, this feature lets to analyze or modify recommendations, avoiding flexibility and personalization problems, which emerges in others recommendation systems.