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Power-law distributions, the h-index, and Google Scholar (GS) citations: a test of their relationship with economics Nobelists

This paper presents proof that Google Scholar (GS) can construct documentary sets relevant for evaluating researchers' works. Nobelists in economics were the researchers under analysis, and two types of tests of the GS cites to their works were performed: distributional and semantic. Distributional tests found that the GS cites to the laureates' works conformed to the power-law model with an asymptote or "tail" conterminous with their h-index demarcating their core oeuvre, validating both GS and the h-index. Semantic tests revealed that their works highest in GS cites were on topics for which they were awarded the prize.

preprint2014arXivOpen access
Stephen J. BensmanAlice DaughertyLawrence J. SmolinskyDaniel S. SageJ. Sylvan Katz
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Open access5 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Stephen J. BensmanAlice DaughertyLawrence J. SmolinskyDaniel S. SageJ. Sylvan Katz

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