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34 clustering coefficient. We were able to verify all of these properties on multiple sites and on a much larger scale in our study. In more recent work, Ahn et al. [6] analyzed complete data from the large South Korean social networking site Cyworld [34], along with data from small sample crawls of MySpace and Orkut. The authors obtained data directly from CyWorld operators, and the volume of available data allows the authors to conduct an in-depth study of that site using some of the same metrics that we use in this thesis. The comparison with different networks, on the other hand, is limited by the small crawled data samples of MySpace and Orkut. Our study is largely complementary: the data available to us for any one site is less detailed, but we are able to compare large crawled data sets from multiple sites. Finally, researchers have also examined how the activity network, or the pattern of interactions between users, compares with the social network. In particular, Wilson et al. [163] studied the activity network of samples of the Facebook network and found that, in contrast to the social network, the activity network is much more sparse and has a significantly lower maximal degree. Chun et al. [29] found similar properties for the interaction network in CyWorld. In our work, we focus only on the social network, but our approach and methods could be naturally applied to the activity network as well.PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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