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The study is based on the “VKontakte” open data. The personal data of users from Vologda region cities, whose age is between 15 and 70 years old, was collected with the help of “VKontakte” API. From the one side, it’s impossible to register in “Vlontakte” for children. From the other side, older generations are not active in social networks. Several filters were developed to exclude fake users. The first is a filter of two weeks. Many fakes are created only for curtain project. They become inactive after the finish of project. So, we can exclude such fake users by the time of the last visit. The second is a filter by the number of subscribers. Fakes usually have huge amounts of subscribers. The third is a filter by the content of status. Fakes often use status for advertising. The last step of data collection was to get subscriptions of users with open pages. A complex users’ characteristics was constructed. It reflects its tastes and interests according to his or her subscribes for social network communities (publics). Topics of “Vlontakte” publics cover significant part of men’s daily life. Most important trends of Russian society discourse are represented there. According to the study of Levada-center, “VKontakte” is still the most popular social net in Russia. A group of users, which tends to subscribe to a certain set of communities is called a pattern of social network behavior. The patterns were defined using the developed method of graph clustering which is based on the force layout of graph (OpenOrd algorithm). Cutting long edges in the OpenOrd algorithm allows to express multiple identity of people in modern society. Eleven obtained patterns of social network behavior were divided in 2 groups: age-sex and thematic. Communities of age-sex patterns have no common subject, they have large number of users, they contain a lot of humorous resources. Communities of thematic patterns have one or two common subjects, they are much less populated, they contain a few number of humorous resources. City’s structure of age-sex patterns depends on its population. City’s structure of thematic patterns is also affected by the composition of its economy. The diversity of city’s social network behavior patterns is directly proportional to its population. The diversity is associated with the role of the services in the local economy for cities with a comparable population.