38. A computer implemented method, the method comprising: repetitively conducting probabilistic percolation crawling at desired time intervals to generate informational network neighborhoods at the desired time intervals, the informational network neighborhood including a community of network nodes linked by referenced links, wherein conducting probabilistic percolation crawling comprises following the one or more reference links in and out of the one or more web pages to one or more neighboring nodes probablistically, wherein performing percolation crawling further comprises randomly selecting reference links in and out of the web page and in and out of the one or more neighboring nodes, wherein selected reference out-links are added to the network neighborhood when the link satisfies a first probability and selected reference in-links are added to the network neighborhood when the link satisfies a second probability, and wherein the communities of network nodes are determined by iteratively partitioning the network neighborhood, wherein each network node includes at least one concept associated with the community, the community comprising a set of network nodes that are more linked amongst themselves than to network nodes that are not included in the community based on the probabilistic percolation crawling; maintaining a representation of the informational network neighborhoods at the desired time intervals in a memory; and identifying changes in the informational network neighborhood by comparing at least two of the informational network neighborhoods maintained in the memory.
38. A computer implemented method, the method comprising: repetitively conducting probabilistic percolation crawling at desired time intervals to generate informational network neighborhoods at the desired time intervals, the informational network neighborhood including a community of network nodes linked by referenced links, wherein conducting probabilistic percolation crawling comprises following the one or more reference links in and out of the one or more web pages to one or more neighboring nodes probablistically, wherein performing percolation crawling further comprises randomly selecting reference links in and out of the web page and in and out of the one or more neighboring nodes, wherein selected reference out-links are added to the network neighborhood when the link satisfies a first probability and selected reference in-links are added to the network neighborhood when the link satisfies a second probability, and wherein the communities of network nodes are determined by iteratively partitioning the network neighborhood, wherein each network node includes at least one concept associated with the community, the community comprising a set of network nodes that are more linked amongst themselves than to network nodes that are not included in the community based on the probabilistic percolation crawling; maintaining a representation of the informational network neighborhoods at the desired time intervals in a memory; and identifying changes in the informational network neighborhood by comparing at least two of the informational network neighborhoods maintained in the memory. 40. The method of claim 38 wherein the changes represent network traffic directed to the community.