The sheer volume of Web data, together with its low signal-to-noise ratio, make it difficult for text-based search engines to locate high-quality pages. Analyzing the links between Web sites has dramatically improved the Web search experience and spawned research into the Webs link structure. This research includes graph-theoretic studies of connectivity, which have shown the Web to have strong similarities with social networks. Self-similarity is pervasive in social networks. While researchers have observed Web self-similarity in other contexts, finding a fractal structure in a graph-theoretic setting adds further evidence to the Webs small-world social nature. Thus, researchers seek to explain and exploit the human behavior implicit in the Webs evolving structure. How can we combine the power of Web networks with networks resulting from other human activity? Accomplishing this goal represents knowledge managements key challenge and opportunity. This article by Ravi Kumar, Prabhakar Raghavan, and others appears in the November 2002 issue of IEEE _Computer_ magazine. [Requires subscription for full text.] The Web and Social Networks | 
