Previous chapters focused on the models of static networks, which consider a relational network at a g iven point in time. Hovewer real-world social networks are dynamic in nature: for example, friends of friends become friends. Social research has, in recent years, paid increasing attention to dynamic and longitudinal network analysis in order to understand network evolution, belief formation, friendship formation, and so on. This chapter focuses mainlv on the dynamics and evolutional patterns of social networks. The chapter introduces real-world applications and reviews major theories and models of dynamic network mining.
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