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Entitymetrics: Measuring the Impact of Entities

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  • Ying Ding
  • Min Song
  • Jia Han
  • Qi Yu
  • Erjia Yan
  • Lili Lin
  • Tamy Chambers

Abstract

This paper proposes entitymetrics to measure the impact of knowledge units. Entitymetrics highlight the importance of entities embedded in scientific literature for further knowledge discovery. In this paper, we use Metformin, a drug for diabetes, as an example to form an entity-entity citation network based on literature related to Metformin. We then calculate the network features and compare the centrality ranks of biological entities with results from Comparative Toxicogenomics Database (CTD). The comparison demonstrates the usefulness of entitymetrics to detect most of the outstanding interactions manually curated in CTD.

Suggested Citation

  • Ying Ding & Min Song & Jia Han & Qi Yu & Erjia Yan & Lili Lin & Tamy Chambers, 2013. "Entitymetrics: Measuring the Impact of Entities," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-14, August.
    • Handle: RePEc:plo:pone00:0071416
    DOI: 10.1371/journal.pone.0071416
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