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220 information sharing networks, ranking systems have proved invaluable for finding rel- evant information – the most well-known example is PageRank for Web documents. However, the content shared in emerging systems like online social networks is dif- ferent from previous systems: the content items rarely have links to other content items; rather, the links connect the users themselves. Thus, a new approach to find- ing relevant information is needed that can compute the reliability of a given piece of information based on the combined reputation of the users who created or endorsed it. Whereas a Web page linked to by nytimes.com is likely important (because many important pages link to nytimes.com), it is unclear whether this same transitive im- portance will apply to links between users. Additionally, since this computation is based on a social network of users, the links between whom may represent shared interest, it may be possible to easily compute customized rankings for each user’s interests. The PeerSpective system represents a first step in this direction, however, the general problem of finding relevant content remains an open challenge.PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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