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9.3.2 Ranking Search engines rank all relevant documents and return the top of the resulting list. Social networks can inform and bias the ranking algorithm, since nearby users in the network often find similar sets of pages relevant. An example we observed is a search with the term “coolstreaming”. A Google search ranks most highly popular sites (such as Wikipedia) discussing the CoolStreaming technique for P2P streaming of multi- media content. PeerSpective ranked the INFOCOM paper describing CoolStreaming at the top, as it is most relevant to our researchers. 9.3.3 Serendipity While browsing the Web, users often discover interesting information by accident, clicking on links that they had not intended to query for. This process, termed serendipity, is an integral part of the Web browsing experience. Search results from PeerSpective provide ample opportunity for such discoveries. For example, while looking for information about “Mu ̈nchen” (Munich), one of our users discovered that a fellow researcher attended school in Mu ̈nchen, thus finding a convenient source of information about the city. 9.4 Summary Online social networking enables new forms of information exchange in the Inter- net. First, end users can very easily and conveniently publish information, without 212PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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