Abstract
As a balanced indicator for both the quality and productivity of researchers’ scientific outputs, h-index suffers severely from loss of significant information in citation distributions so that its ability to discriminate researchers is rather limited. H-index not only fails to distinguish researchers with quasi the same h-values, but also lacks the ability to promote researchers’ foci on originality and high quality. Current extensions to h-index by exploiting citation distribution characteristics all exhibit some “pathologically” eccentric behaviors against either real datasets or theoretical distributions. With a motivation of balancing quality and quantity, this paper proposes a new h-type index h*pt by exploiting citation distribution characteristics, which encourages quality by defining reward/penalty factors to excess/long-tail citations, and at the same time balances productivity by scaling citations outside the h-core to the average performance of the long-tail papers. Extensive experiments on both the ACL Anthology Network dataset and several theoretical citation distributions prove that the proposed h*pt achieves reasonably better results than previous h-type extensions.
Translated title of the contribution | h*pt: An h-type index encouraging quality and balancing productivity |
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Original language | Chinese (Simplified) |
Number of pages | 13 |
Publication status | Published - Jan 2017 |
Keywords
- h*pt-index
- h-index
- citation distribution
- research evaluation
- qualitative indicator