Estimating Thematic Similarity of Scholarly Papers with Their Resistance Distance in an Electric Network Model

Alexander Struck; Frank Havemann; Jochen Gl\"aser; Michael Heinz

arxiv: 1303.0089 · v1 · pith:CMB6C3GAnew · submitted 2013-03-01 · 💻 cs.DL · cs.SI· physics.soc-ph

Estimating Thematic Similarity of Scholarly Papers with Their Resistance Distance in an Electric Network Model

Frank Havemann , Michael Heinz , Jochen Gl\"aser , Alexander Struck This is my paper

classification 💻 cs.DL cs.SIphysics.soc-ph

keywords citationresistanceciteddistanceelectricnetworknumberthematic

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We calculate resistance distances between papers in a nearly bipartite citation network of 492 papers and the sources cited by them. We validate that this is a realistic measure of thematic distance if each citation link has an electric resistance equal to the geometric mean of the number of the paper's references and the citation number of the cited source.

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Estimating Thematic Similarity of Scholarly Papers with Their Resistance Distance in an Electric Network Model

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