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Paper de cientometria quentinho do forno


We discuss centrality indexes in the bipartite scientific papers-authors networks.

We propose a new index (the K-index), which is simple to calculate and outperforms the Hirsch h-index in several aspects.

The K-index correlates better with Nobel prizes than any of the other indexes furnished by the Web of Science (WoS) platform.

The K-index is related to connections to the hubs of the scientific citation and social networks.

The outliers in the K vs h plane contain interesting information that can be used for scientific prizes prediction.


We introduce a new centrality index for bipartite network of papers and authors that we call K-index. The K-index grows with the citation performance of the papers that cite a given researcher and can seen as a measure of scientific social recognition. Indeed, the K-index measures the number of hubs, defined in a self-consistent way in the bipartite network, that cites a given author. We show that the K-index can be computed by simple inspection of the Web of Science platform and presents several advantages over other centrality indexes, in particular Hirsch h-index. The K-index is robust to self-citations, is not limited by the total number of papers published by a researcher as occurs for the h-index and can distinguish in a consistent way researchers that have the same h-index but very different scientific social recognition. The K-index easily detects a known case of a researcher with inflated number of papers, citations and h-index due to scientific misconduct. Finally, we show that, in a sample of twenty-eight physics Nobel laureates and twenty-eight highly cited non-Nobel-laureate physicists, the K-index correlates better to the achievement of the prize than the number of papers, citations, citations per paper, citing articles or the h-index. Clustering researchers in a K versus h plot reveals interesting outliers that suggest that these two indexes can present complementary independent information.


Hirsch index
Lobby index
Complex networks
Node centrality
Citation network
Web of science
Social recognition
Scientific prizes
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