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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An automatic method to generate domain-specific investigator networks using PubMed abstracts
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2007
|
| DOI | 10.1186/1472-6947-7-17 |
| Pubmed ID | |
| Authors |
Wei Yu, Ajay Yesupriya, Anja Wulf, Junfeng Qu, Marta Gwinn, Muin J Khoury |
| Abstract |
Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 50% |
| Canada | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 50% |
| Members of the public | 1 | 25% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 20% |
| Mexico | 2 | 4% |
| Austria | 1 | 2% |
| Germany | 1 | 2% |
| Switzerland | 1 | 2% |
| Poland | 1 | 2% |
| Unknown | 35 | 69% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 27% |
| Professor | 7 | 14% |
| Student > Ph. D. Student | 7 | 14% |
| Student > Master | 5 | 10% |
| Other | 5 | 10% |
| Other | 9 | 18% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 29% |
| Medicine and Dentistry | 11 | 22% |
| Agricultural and Biological Sciences | 6 | 12% |
| Social Sciences | 4 | 8% |
| Arts and Humanities | 2 | 4% |
| Other | 8 | 16% |
| Unknown | 5 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 March 2015.
All research outputs
#6,391,095
of 23,577,654 outputs
Outputs from BMC Medical Informatics and Decision Making
#579
of 2,025 outputs
Outputs of similar age
#21,849
of 69,709 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 5 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,025 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 69,709 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.