SOCIAL NETWORK SOFTWARE ANALYSIS

In recent years, the problem of social network analysis has moved from the formal theory of sociological research to the modern strategy of social structure research. Social network analysis can be used to predict the behavior of social elements-network participants, determine the specifics of their interaction, and classify social network participants.
Due to the rapid development of information, as well as mobile technologies, modern people have the opportunity to virtual communication using various social networks. Getting information about the behavior of actors in such social networks opens up opportunities for quick and convenient analysis of social structures. Often, for a software developer, the task of introducing a ready-made software product to the market, as well as the prospects for its development, is complicated by a lack of understanding of the current market situation. The ability to identify a group of target users, consider their advantages and disadvantages in the context of competing products, as well as user opinions based on information obtained through the analysis of social units, is very valuable for software developers and distributors. Therefore, the use of social network analysis to identify groups of target users of the software product is relevant.
This paper presents a review of theoretical and applied research on the evolution and analysis of social networks. A brief description of some popular social networks is provided, as well as individual web services and software applications for their analysis. The problem of finding user groups for the implemented software product using social networks is considered. To solve this problem, we analyze the main methods and approaches to the study of social networks. The method involves checking the set obtained from clustering results. The resulting set is displayed on the set of users of the software product. The developed method makes it possible to identify users of the software product based on the analysis of social network content.

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