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Optimal Ranking In Networks With Community Structure
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Category : Web Search Engines » Google
average Google rank of community webpages depends on the degree to which it is . ture of client's webpages to improve their Google rank. .
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Content Summary :
The World-Wide Web (WWW) is characterized by a strong community structure in which groups of webpages (e.g. those devoted to a common topic or belonging to the same organization) aredensely interconnected by hyperlinks. We study how such network architecture affects the averageGoogle rank of individual communities. Using a mean-field approximation, we quantify how theaverage Google rank of community webpages depends on the degree to which it is isolated from therest of the world in both incoming and outgoing directions, and α – the only intrinsic parameter ofGoogle’s PageRank algorithm. Based on this expression we introduce a concept of a web-communitybeing decoupled or conversely coupled to the rest of the network. We proceed with empirical studyof several internal web-communities within two US universities. The predictions of our mean-fieldtreatment were qualitatively verified in those real-life networks. Furthermore, the value α = 0.15used by Google seems to be optimized for the degree of isolation of communities as they exist in theactual WWW.
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