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The h’-Index, Effectively Improving the h-Index Based on the Citation Distribution

Overview of attention for article published in PLOS ONE, April 2013
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Title
The h’-Index, Effectively Improving the h-Index Based on the Citation Distribution
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0059912
Pubmed ID
Authors

Chun-Ting Zhang

Abstract

Although being a simple and effective index that has been widely used to evaluate academic output of scientists, the h-index suffers from drawbacks. One critical disadvantage is that only h-squared citations can be inferred from the h-index, which completely ignores excess and h-tail citations, leading to unfair and inaccurate evaluations in many cases.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Colombia 1 2%
United States 1 2%
Unknown 46 94%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 8 16%
Student > Doctoral Student 7 14%
Student > Ph. D. Student 5 10%
Student > Master 4 8%
Student > Bachelor 3 6%
Other 13 27%
Unknown 9 18%
Readers by discipline Count As %
Social Sciences 8 16%
Medicine and Dentistry 7 14%
Computer Science 5 10%
Agricultural and Biological Sciences 3 6%
Business, Management and Accounting 3 6%
Other 13 27%
Unknown 10 20%