Social engineering attacks based on the human factor have long been the most frequently used in violation of the information security policies. One of the ways to increase the organization's level of protection against social engineering attacks is building a social graph of the organization's employees and its analysis. The nodes of such graph associated with users of the information system, and edge designate the relationships between them. Moreover, this kind of information can be obtained by analyzing social networks. However, often users have accounts in different social networks, and the information presented in them is different. The purpose of this article became to propose approaches to merging probabilistic estimates of the relationship between users, which are linguistic values of linguistic variable "type of relationship". The theoretical significance of the results lies in the proposal of new approaches to the merging of probabilistic estimates of linguistic variables, the practical significance consist in creating the basis for further analysis of the social graph of the organization's employees, in particular, for detecting the most critical trajectories of attack development or solving backtracking tasks of social engineering attacks, e.i. the investigation of cyber crime committed by using social engineering techniques.