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A graph is an abstraction for modeling relationships between things. Different types of graph can be used to model real networks, depending on their characteristics. Main goal of this paper is to analyze performances of one of the most widely applied algorithms for clusterization of graphs, Girvan – Newman algorithm, on different types of randomly generated graphs in order to see what type of graph is the most appropriate to use in real world example.