Advanced search
Start date
Betweenand
Related content
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A simple centrality index for scientific social recognition

Full text
Author(s):
Kinouchi, Osame [1] ; Soares, Leonardo D. H. [1] ; Cardoso, George C. [1]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Dept Fis, FFCLRP, BR-14040901 Ribeirao Preto - Brazil
Total Affiliations: 1
Document type: Journal article
Source: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 491, p. 632-640, FEB 1 2018.
Web of Science Citations: 0
Abstract

We introduce a new centrality index for bipartite networks 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 be 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. (C) 2017 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:Oswaldo Baffa Filho
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC