Social networking sites (Facebook, Twitter, Instagram, etc.) are widely used digital platforms for communication and interaction between billions of people. Data about users’ interaction is stored in a structured and computer readable format, which makes possible (with the appropriate consent of the people whose data are) to process it, analyze and come up with various conclusions. The availability of data about people’s interaction is the foundation for all social networks' researches – both sociological and psychological, as well as those in the field of computer science. In this doctoral thesis a number of social surveys were conducted (with the appropriate consent of the examinees) and reference datasets for social network researches were collected. Datasets contain data about users’ interaction on the social networking site Facebook and users’ estimation of the relationship intensities with their Facebook friends. Collected reference datasets are analyzed in detail. By using a reference dataset, a model for computing social distance based on people's interaction data on Facebook is designed, implemented, fine-tuned and verified. Unlike previous researches showing the intensity of interpersonal relations by applying the concept of weight or tie strength, social distance is an innovative way of expressing the intensity of relationship between people through the concept of distance. The main feature of the concept of distance is that the higher intensity is shown by the smaller number. It is very suitable for further applications such as determining the propagation information time or determining the user’s approximate geographic location. Thesis defines model of enriched social graph. Enriched social graph is formal representation of social network, i.e. formal representation of relations between people. Enriched social graph can record different types of interpersonal relations and their intensities. Intensity of interpersonal relations is shown as their social distance, which is calculated by using model previously introduced in this thesis.