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78 In this chapter, we characterize the structural properties of four online social net- works. We compare the networks to each other, and we compare their properties with those previously observed for the Web. The Web is one of the most well-studied online networks, and our study shares much of its methodology with previous studies of the Web. Thus, it is perhaps natural to tend to compare our results with the structure of the Web. However, we are well aware that the user graph in social networks is fundamentally different from the interconnection of web pages; our comparisons serve more to calibrate our results than to point out (expected) differences. The focus of our work is the social network users within the sites we study. More specifically, we study the properties of the large WCC in the user graphs of four popular sites. We do not attempt to study the entire user community (which would include users who do not use the social networking features), information flow, or workload of online social networking sites. While these topics are important, they are beyond the scope of this thesis. 5.1 High-level data statistics Table 5.1 presents the high-level statistics of the four networks we examine in this chapter. The crawled network sizes vary by almost a factor of five (1.1 million users in YouTube versus 5.2 million in LiveJournal), and the number of links varies by al- most two orders of magnitude (4.9 million in YouTube versus 223 million in Orkut). Similarly, other metrics such as the average number of friend links per node and userPDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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