Measures of research impact
An Impact Factor is one measure of the relative importance of a journal or scientist to science and social science literature and research.
Each index or uses a different methodology and produces slightly different results, revealing the importance of using several sources to judge the true impact of a journal's or scientist’s work.
Careful use of these impact data is essential, and should be based on a thorough understanding of the methodology used to generate impact factors. There are controversial aspects of using impact factors:
- It is not clear whether the number of times a paper is cited measures its actual quality.
- Some databases that calculate impact factors fail to incorporate publications such as textbooks, handbooks and reference books.
- Certain disciplines have low numbers of journals and usage. For this reason, one should only compare journals or researchers within the same discipline.
- Review articles normally are cited more often and therefore can skew results.
- Self-citing may skew results.
- Some resources used to calculate impact factors have inadequate international coverage.
- Editorial policies can artificially inflate an impact factor.
Comments (0)
Which measure do you use?
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Journal citation |
Eigenfactor |
H-index |
| Measure of journal(s) impact | X | X | |
| Includes theses & popular magazines | X | ||
| Considers quality of citing journal | X | ||
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Adjusts for disciplinary patterns, permitting cross-discipline comparisons |
X | ||
| Measure of author impact | X | ||
| Uses 2 years of data | X | ||
| Uses 5 years of data | X | ||
| Uses all published years/articles | X |
Engineering/Math Librarian |
Links: Profile & Guides |

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