EFFECTS OF COMMUNITY STRUCTURE ON SEARCH AND RANKING IN COMPLEX NETWORKS
The community structure in complex networks has been a popular topic in recent literature. It is present in all types of complex networks ranging from bio-molecular networks, where it reflects functional associations between proteins to information networks such as the The World Wide Web (WWW). The World Wide Web – a quintessential large complex network – presents formidable challenge for the efficient information retrieval and ranking. Google has reached its current position as the world’s most popular search engine by efficient and ingenious utilization of topological properties of this WWW network for ranking of individual webpages. The topological structure of the WWW network is characterized by a strong community structure in which groups of webpages (e.g. those devoted to a common topic) are densely interconnected by hyperlinks. We study how such network architecture affects the average Google ranking of individual webpages in the community. We demonstrate that the Google rank of community webpages could either increase or decrease with the density of inter-community links depending on the exact balance between average in- and out-degrees in the community.
KeywordsBrookhaven National Laboratory Community Node Exact Balance Popular Search Engine Random Surfer
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