Abstract
Groups – social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we can use this information and try to predict the next step in the given group evolution. In the paper, a new aproach for group evolution prediction is presented and examined. Experimental studies on four evolving social networks revealed that (i) the prediction based on the simple input features may be very accurate, (ii) some classifiers are more precise than the others and (iii) parameters of the group evolution extracion method significantly influence the prediction quality.
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Bródka, P., Kazienko, P., Kołoszczyk, B. (2012). Predicting Group Evolution in the Social Network. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., Guéret, C. (eds) Social Informatics. SocInfo 2012. Lecture Notes in Computer Science, vol 7710. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35386-4_5
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DOI: https://doi.org/10.1007/978-3-642-35386-4_5
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