Generalized h-index for Disclosing Latent Facts in Citation Networks

TL;DR

This paper introduces generalized variants of the h-index to better evaluate scientific impact and prestige, revealing influential researchers and venues regardless of age through extensive experiments on DBLP.

Contribution

It develops new generalized citation indices that improve upon the traditional h-index for ranking scientists and publication venues.

Findings

New indices effectively identify trendsetters and influential researchers.

Generalized metrics outperform traditional h-index in revealing impactful scientists.

Experimental validation on DBLP demonstrates the indices' robustness and usefulness.

Abstract

What is the value of a scientist and its impact upon the scientific thinking? How can we measure the prestige of a journal or of a conference? The evaluation of the scientific work of a scientist and the estimation of the quality of a journal or conference has long attracted significant interest, due to the benefits from obtaining an unbiased and fair criterion. Although it appears to be simple, defining a quality metric is not an easy task. To overcome the disadvantages of the present metrics used for ranking scientists and journals, J.E. Hirsch proposed a pioneering metric, the now famous h-index. In this article, we demonstrate several inefficiencies of this index and develop a pair of generalizations and effective variants of it to deal with scientist ranking and with publication forum ranking. The new citation indices are able to disclose trendsetters in scientific research, as well as researchers that constantly shape their field with their influential work, no matter how old they are. We exhibit the effectiveness and the benefits of the new indices to unfold the full potential of the h-index, with extensive experimental results obtained from DBLP, a widely known on-line digital library.