Title |
Entitymetrics: Measuring the Impact of Entities
|
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Published in |
PLOS ONE, August 2013
|
DOI | 10.1371/journal.pone.0071416 |
Pubmed ID | |
Authors |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 2 | 22% |
Brazil | 1 | 11% |
United Kingdom | 1 | 11% |
Unknown | 5 | 56% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 44% |
Scientists | 4 | 44% |
Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 4% |
Spain | 2 | 2% |
Mexico | 2 | 2% |
Malaysia | 1 | <1% |
France | 1 | <1% |
Brazil | 1 | <1% |
Nigeria | 1 | <1% |
Unknown | 94 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 23 | 22% |
Student > Master | 12 | 11% |
Librarian | 9 | 8% |
Researcher | 8 | 8% |
Student > Doctoral Student | 6 | 6% |
Other | 23 | 22% |
Unknown | 25 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 29 | 27% |
Social Sciences | 18 | 17% |
Business, Management and Accounting | 4 | 4% |
Medicine and Dentistry | 4 | 4% |
Arts and Humanities | 3 | 3% |
Other | 21 | 20% |
Unknown | 27 | 25% |