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We present a technique to represent the structure of large social networks through ego-centered network neighborhoods. This provides a local view of the network, focusing on the vertices and their kth order neighborhoods allowing discovery of interesting patterns and features of the network that would be hidden in a global network analysis. We present several examples from a corporate phone call network revealing the ability of our methods to discover interesting network behavior that is only available at the local level. In addition, we present an approach to use these concepts to identify abrupt or subtle anomalies in dynamic networks.