Emergence of innovations in networked populations with reputation-driven interactions

Pablo Gallarta-Sáenz; Hugo Pérez-Martínez; Jesús Gómez-Gardeñes

doi:10.1063/5.0189505

Emergence of innovations in networked populations with reputation-driven interactions

Chaos. 2024 Mar 1;34(3):033106. doi: 10.1063/5.0189505.

Authors

Pablo Gallarta-Sáenz^{1

2}, Hugo Pérez-Martínez^{1

2}, Jesús Gómez-Gardeñes^{1

2

3}

Affiliations

¹ Department of Condensed Matter Physics, University of Zaragoza, 50009 Zaragoza, Spain.
² GOTHAM lab, Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018 Zaragoza, Spain.
³ Center for Computational Social Science, University of Kobe, 657-8501 Kobe, Japan.

PMID: 38437870
DOI: 10.1063/5.0189505

Abstract

In this work, we analyze how reputation-based interactions influence the emergence of innovations. To do so, we make use of a dynamic model that mimics the discovery process by which, at each time step, a pair of individuals meet and merge their knowledge to eventually result in a novel technology of higher value. The way in which these pairs are brought together is found to be crucial for achieving the highest technological level. Our results show that when the influence of reputation is weak or moderate, it induces an acceleration of the discovery process with respect to the neutral case (purely random coupling). However, an excess of reputation is clearly detrimental, because it leads to an excessive concentration of knowledge in a small set of people, which prevents a diversification of the technologies discovered and, in addition, leads to societies in which a majority of individuals lack technical capabilities.