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Description: Identifying communities in social networks is one of the most important tasks nowadays. Social networks are especially relevant for networks represented by large-scale graphics. At the same time, it is important to use approximate methods that lead to near-optimal rather than optimal results within a given time. In this article, we propose to extract the communities based on the method of maximum likelihood similarity by representing them by letters. The community structure search algorithm is described and the performance of the algorithm is illustrated using examples of different views of the octagonal network.. Calculations were carried out using the Maple program.