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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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2.2.2 Shared interest Adjacent users in a social network also tend to share common interests. Users browse neighboring regions of their social network because they are likely to find content that is of interest to them. Systems such as Yahoo My Web [165], Google Co-op [60], and PeerSpective [104] use social networks to rank Internet search results relative to the interests of a user’s social network. Using the content viewed and search results clicked on by members of a social network, these systems to rank the results of the members’ future searches more accurately. Clearly, understanding the structure of online social networks, as well as the pro- cesses that shape them, is important for these applications. For example, efficient algorithms are needed for inferring the actual degree of shared interest between two users, or the reliability of a user (as perceived by other users). It is also important to understand the robustness of such networks to deliberate attempts of manipu- lation. These topics are beyond the scope of this thesis; however, a fundamental understanding of online social network structure is likely to be a necessary first step. 2.2.3 Content exchange The phenomenal popularity of social networking sites like YouTube, Flickr, and MyS- pace represents a shift in how content is published, located, and distributed on the Internet. Understanding how content diffuses through these networks and becomes popular over time is not only of academic interest, but is increasingly important in 20

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