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Social communities are important components of entire societies, analyzed by means of the social network concept. Their immanent feature is continuous evolution over time. If user's know how groups in the social network has evolved user's can use this information and try to predict the next step in the given group evolution. In the paper, a new approach for group evolution prediction is presented and examined. Experimental studies on four evolving social networks revealed that the prediction based on the simple input features may be very accurate, some classifiers are more precise than the others and parameters of the group evolution extraction method significantly influence the prediction quality.
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