Entitymetrics: Measuring the Impact of Entities

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

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)

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.

Original languageEnglish
Article numbere71416
JournalPloS one
Volume8
Issue number8
DOIs
Publication statusPublished - 2013 Aug 29

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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