Comparing the influence of ecology journals using citation-based indices: making sense of a multitude of metrics

The links among scholarly citations creates a tremendous network that reveals patterns of influence and flows of ideas. The systematic evaluation of these networks can be used to create aggregate measures of journal influence. To understand the citation patterns and compare influence among ecology...

Full description

Bibliographic Details
Main Author: Daniel J Hocking
Format: Article
Language:English
Published: Queen's University 2013-11-01
Series:Ideas in Ecology and Evolution
Subjects:
Online Access:https://ojs.library.queensu.ca/index.php/IEE/article/view/4949
Description
Summary:The links among scholarly citations creates a tremendous network that reveals patterns of influence and flows of ideas. The systematic evaluation of these networks can be used to create aggregate measures of journal influence. To understand the citation patterns and compare influence among ecology journals, I compiled 11 popular metrics for 110 ecology journals: Journal Impact Factor (JIF), 5-year Journal Impact Factor (JIF5), Eigenfactor, Article Influence (AI), Source-Normalized Impact per Paper (SNIP), SCImago Journal Report (SJR), h-index, hc-index, e-index, g-index, and AR-index. All metrics were positively correlated among ecology journals; however, there was still considerable variation among metrics. Annual Review of Ecology, Evolution, and Systematics, Trends in Ecology and Evolution, and Ecology Letters were the top three journals across metrics on a per article basis. Proceedings of the Royal Society B, Ecology, and Molecular Ecology had the greatest overall influence on science, as indicated by the Eigenfactor. There was much greater variability among the other metrics because they focus on the mostly highly cited papers from each journal. Each influence metric has its own strengths and weaknesses, and therefore its own uses. Researchers interested in the average influence of articles in a journal would be best served by referring to AI scores. Despite the usefulness of citation-based metrics, they should not be overly emphasized by publishers and they should be avoided by granting agencies and in personnel decisions. Finally, citation-based metrics only capture one aspect of scientific influence, they do not consider the influence on legislation, land-use practices, public perception, or other effects outside of the publishing network.
ISSN:1918-3178