Title |
The "impact factor" revisited
|
---|---|
Published in |
Biomedical Digital Libraries, December 2005
|
DOI | 10.1186/1742-5581-2-7 |
Pubmed ID | |
Authors |
Peng Dong, Marie Loh, Adrian Mondry |
Abstract |
The number of scientific journals has become so large that individuals, institutions and institutional libraries cannot completely store their physical content. In order to prioritize the choice of quality information sources, librarians and scientists are in need of reliable decision aids. The "impact factor" (IF) is the most commonly used assessment aid for deciding which journals should receive a scholarly submission or attention from research readership. It is also an often misunderstood tool. This narrative review explains how the IF is calculated, how bias is introduced into the calculation, which questions the IF can or cannot answer, and how different professional groups can benefit from IF use. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 8 | 3% |
Germany | 7 | 2% |
Sweden | 5 | 2% |
United Kingdom | 3 | 1% |
Brazil | 3 | 1% |
Colombia | 2 | <1% |
Malaysia | 2 | <1% |
Portugal | 2 | <1% |
France | 2 | <1% |
Other | 13 | 5% |
Unknown | 237 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 57 | 20% |
Student > Ph. D. Student | 38 | 13% |
Professor | 37 | 13% |
Student > Master | 31 | 11% |
Professor > Associate Professor | 23 | 8% |
Other | 74 | 26% |
Unknown | 24 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 63 | 22% |
Medicine and Dentistry | 47 | 17% |
Social Sciences | 31 | 11% |
Computer Science | 20 | 7% |
Psychology | 10 | 4% |
Other | 78 | 27% |
Unknown | 35 | 12% |