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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200 effective, because the incident links to a page are strong indicators of the importance or relevance of the page’s content in the eyes of other users. However, hyperlink-based search has some well known limitations. First, while Web search is very effective for relatively static information, it may under-rate or miss recently published content. For a new page to be noticed and appropriately ranked by a search engine, (a) it must be discovered and indexed by the search engine, (b) hyperlinks to the new page must be included in subsequently published or edited pages, and (c) all such links must then be discovered by the search engine. Second, as search engines determine the relevance of a page by its incident hyper- links, their rating reflects the interests and biases of the Web community at large. For instance, a search for “Michael Jackson” yields mostly pages with information about the pop star. Computer scientists, however, may find the Web page of a professor with the same name more relevant. Refining the search to find that page is possible but can be tricky, particularly if one does not recall the professor’s current affiliation or field of specialization. Third, the hyperlink structure influences whether a page is included in a search engine’s index. Unlinked pages and non-publicly accessible pages are not indexed. Many other pages are not indexed because the search engine deems them insufficiently relevant, due to their location in the hyperlink structure. As a result, obscure, special- interest content is less likely to be accessible via Web search.

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