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Correction: Xiang, Y.M.; Pan, W.F.; Jiang, H.B.; Zhu, Y.F.; Li, H. Measuring Software Modularity Based on Software Networks. Entropy 2019, 21, 344

Gintropy: Gini Index Based Generalization of Entropy

Wigner Research Centre for Physics, 1121 Budapest, Hungary
Complexity Science Hub, 1080 Vienna, Austria
Department of Physics, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Author to whom correspondence should be addressed.
Entropy 2020, 22(8), 879;
Received: 9 July 2020 / Revised: 7 August 2020 / Accepted: 8 August 2020 / Published: 10 August 2020
(This article belongs to the Section Multidisciplinary Applications)
Entropy is being used in physics, mathematics, informatics and in related areas to describe equilibration, dissipation, maximal probability states and optimal compression of information. The Gini index, on the other hand, is an established measure for social and economical inequalities in a society. In this paper, we explore the mathematical similarities and connections in these two quantities and introduce a new measure that is capable of connecting these two at an interesting analogy level. This supports the idea that a generalization of the Gibbs–Boltzmann–Shannon entropy, based on a transformation of the Lorenz curve, can properly serve in quantifying different aspects of complexity in socio- and econo-physics. View Full-Text
Keywords: entropy; Gini index; socio-economic inequalities; econophysics entropy; Gini index; socio-economic inequalities; econophysics
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MDPI and ACS Style

Biró, T.S.; Néda, Z. Gintropy: Gini Index Based Generalization of Entropy. Entropy 2020, 22, 879.

AMA Style

Biró TS, Néda Z. Gintropy: Gini Index Based Generalization of Entropy. Entropy. 2020; 22(8):879.

Chicago/Turabian Style

Biró, Tamás S., and Zoltán Néda. 2020. "Gintropy: Gini Index Based Generalization of Entropy" Entropy 22, no. 8: 879.

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