  Information on any given topic is often scattered across the web. Previously
this scatter has been characterized through the distribution of a set of facts
(i.e. pieces of information) across web pages, showing that typically a few
pages contain many facts on the topic, while many pages contain just a few.
While such approaches have revealed important scatter phenomena, they are lossy
in that they conceal how specific facts (e.g. rare facts) occur in specific
types of pages (e.g. fact-rich pages). To reveal such regularities, we
construct bi-partite networks, consisting of two types of vertices: the facts
contained in webpages and the webpages themselves. Such a representation
enables the application of a series of network analysis techniques, revealing
structural features such as connectivity, robustness, and clustering. We
discuss the implications of each of these features to the users' ability to
find comprehensive information online. Finally, we compare the bipartite graph
structure of webpages and facts with the hyperlink structure between the
webpages.
