As the development of economic today, Bank business deeply integrates into our lives. Thousands of transactions generate the large amounts of data. Traditional bank customer management system simply classifies and counts these data, and the system is deficient in customer relationship management. However, the social network model can provide the influence between the bank customers for the bank. In this paper, we construct a social network by calculating the relationship between bank customers. In order to explore how bank customers in the bank customer network affect each other, we use three indicators: the average path length L, clustering coefficient C and degree distribution p (x) to conduct a comprehensive analysis. Consequently, we find that there evidently exist influential customers in this network.
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