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Explanatory growth models Some recent studies, particularly on online social networks, have proposed explana- tory models of the network growth. Unlike structural growth models, which try to model growth solely as a function of the network structure, explanatory models seek to account for the underlying sociological factors that cause the links to be established. For example, an explanatory growth model for Flickr, a photo-sharing social network, could be based on an understanding of how users behave when sharing pictures. Examples of work on explanatory growth models include Kumar [82], who divided users into ones who are active and passive, and presented a model describing their behavior in an online social network. Jin et al. [70] presented a model of social net- works based on known human interactions. Backstrom et al. [12] looked at snapshots of group membership in LiveJournal, and presented a model for the growth of user groups over time based on understandings of peer pressure. Finally, Chang et al. [27] proposed a model for the growth in connectivity of the Internet topology, modeling the decision processes of the administrators of autonomous systems. Compared to structural growth models, explanatory models are more detailed, but they also tend to be specific to the network being investigated. For example, the reasons why autonomous systems connect to each other in the Internet topology are very different from the reasons why users in Flickr connect to each other. By being agnostic to these factors, structural growth models are inherently less accurate. But, they are far more general, and can be compared across different types of networks. 38PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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