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3.2 Complex network growth In addition to the study of the static structure of various information networks, re- searchers have also examined the evolution of networks, looking at the processes by which links are formed and removed. Consistent with previous work, we refer to these processes as growth models. In our work, we collect detailed data on the growth of online social networks. Thus, in this section, we describe related work on various growth models, and detail the extent to which they have been validated on real data. 3.2.1 Growth models Growth models for complex networks can be partitioned into structural models (i.e., models that only take into account the structure of the network to predict link forma- tion or removal) and explanatory models (i.e., models that consider external factors, such as human factors in online social networks, to predict links). We describe each of these types of models below. Structural growth models Researchers sought to explain the intriguing similarity in the high-level structural properties across networks of very different scales and types by hypothesizing that the networks are the result of a few common structural growth processes at work. Many models of these processes have been proposed and analyzed to explain the structure of complex networks. 36PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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