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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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90 YouTube is due its more “celebrity”-driven nature; there are a few extremely popular users on YouTube to whom many unpopular users connect. To quantitatively explore this phenomenon, we next examine two metrics based on the joint degree distribution: the scale-free metric s and the assortativity r. 5.6.2 Scale-free behavior The scale-free metric of the networks are shown in the legend of Figure 5.6. All of the networks with the exception of YouTube show a significant s, indicating that high-degree nodes tend to connect to other high-degree nodes, and low-degree nodes tend to connect to low-degree nodes. 5.6.3 Assortativity The scale-free metric is related to the assortativity coefficient r, which is a measure of the likelihood for nodes to connect to other nodes with similar degrees. Recent work has suggested that the scale-free metric is more suitable for comparing the structure of different graphs [8], as it takes into account the possible configurations of networks with properties including connectedness and no self-loops. However, for completeness, we calculated the assortativity coefficients for each of the networks, and found 0.202 for Flickr, 0.179 for LiveJournal, 0.072 for Orkut, and -0.033 for YouTube. The assortativity shows yet another difference between the social networks and other previously observed power-law networks. For example, the Web and the In- ternet have both been shown to have negative assortativity coefficients of -0.067 and

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