  Evolving graphs arise in problems where interrelations between data change
over time. We present a breadth first search (BFS) algorithm for evolving
graphs that computes the most direct influences between nodes at two different
times. Using simple examples, we show that naive unfoldings of adjacency
matrices miscount the number of temporal paths. By mapping an evolving graph to
an adjacency matrix of an equivalent static graph, we prove that our
generalization of the BFS algorithm correctly accounts for paths that traverse
both space and time. Finally, we demonstrate how the BFS over evolving graphs
can be applied to mine citation networks.

Social and Information Networks;Data Structures and Algorithms;Numerical Analysis