"The structure of those networks can tell you quite a lot about how the systems work, but they're far too big to analyze by just putting dots on a piece of paper and drawing lines to connect them," said Mark Newman, an assistant professor of physics and complex systems at the University of Michigan. One challenge in making sense of a large network is finding clumps---or communities---of members that have something in common, such as Web pages that are all about the same topic, people that socialize together or animals that eat the same kind of food. Newman and collaborator Michelle Girvan, a postdoctoral fellow at the Santa Fe Institute in Santa Fe, New Mexico, have developed a new method for finding communities that reveals a lot about the structure of large, complex networks... "The way most people have approached the problem is to look for the clumps themselves---to look for things that are joined together strongly," said Newman. "We decided to approach it from the other end," by searching out and then eliminating the links that join clumps together. "When we remove those from the network, what we're left with is the clumps."