EqRank: Theme Evolution in Citation Graphs
G. B. Pivovarov, S. E. Trunov
Abstract
Time evolution of the classification scheme generated by the EqRank algorithm is studied with hep-th citation graph as an example. Intuitive expectations about evolution of an adequate classification scheme for a growing set of objects are formulated. Evolution compliant with these expectations is called natural. It is demonstrated that EqRank yields a naturally evolving classification scheme. We conclude that EqRank can be used as a means to detect new scientific themes, and to track their development.
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