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We present a method that utilises dynamic molecular modelling technique to track the changes within complex social network. The users forming a social network are interpreted as large sets of interacting particles. The data for the conducted research was obtained from e-mail communication within Enron company. The social network of employees was extracted and used to evaluate the methodology of social network dynamics modelling.