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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems

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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems ( online-social-networks-measurement-analysis-and-applications )

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113 created link, we computed the expected distance from the source to the destination, if the destination is chosen using the BA model. Figure 6.5 also plots this distribution for each network. In all five networks that we study, the observed distances between the source and destination of links shows a significant bias towards nearby nodes, relative to what the BA model would predict. In fact, in Flickr, Wikipedia, and YouTube-D, we found that the number of new links connecting 2-hop neighbors in the empirical data exceeded that predicted by the BA model by a factor of three. This result shows that while new link formation in our observed networks follows preferential attachment, the link creation process cannot be explained by the BA model alone. Nodes are far more likely to link to nearby nodes than the model would suggest. This result is consistent with the previous observations on static networks, which showed that the clustering coefficient was significant higher than would be predicted by the BA model. In the next section, we focus on how nodes choose which nearby node to link to. 6.6 Mechanisms causing proximity bias In the previous section, we showed that newly created links show a strong bias towards nodes which are close together, relative to what the BA model would predict. This suggests that an alternate mechanism is causing the establishment of new links. In this section, we take a closer look at the newly created links, and see if the growth

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