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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems Alan E. Mislove Abstract Recently, online social networking sites have exploded in popularity. Numerous sites are dedicated to finding and maintaining contacts and to locating and sharing different types of content. Online social networks represent a new kind of information network that differs significantly from existing networks like the Web. For example, in the Web, hyperlinks between content form a graph that is used to organize, navigate, and rank information. The properties of the Web graph have been studied extensively, and have lead to useful algorithms such as PageRank. In contrast, few links exist between content in online social networks and instead, the links exist between content and users, and between users themselves. However, little is known in the research community about the properties of online social network graphs at scale, the factors that shape their structure, or the ways they can be leveraged in information systems. In this thesis, we use novel measurement techniques to study online social net- works at scale, and use the resulting insights to design innovative new information systems. First, we examine the structure and growth patterns of online social net-PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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