The World Wide Web provides a unprecedented opportunity to automatically analyze a large sample of interests and activity in the world. We discuss methods for extracting knowledge from the web by randomly sampling and analyzing hosts and pages, and by analyzing the link structure of the web and how links accumulate over time. A variety of interesting and valuable information can be extracted, such as the distribution of web pages over domains, the distribution of interest in different areas, communities related to different topics, the nature of competition in different categories of sites, and the degree of communication between different communities or countries.
The World Wide Web has become an important knowledge and communication resource. As more people use the web for more tasks, it provides an increasingly representative and unprecedented in scale machine-readable sample of interests and activity in the world.
However, the distributed and heterogeneous nature of the web makes large-scale analysis difficult. We provide an overview of recent methods for analyzing and extracting knowledge from the web, along with samples of the knowledge that can be extracted.