The Matthew effect in empirical data

By Matjaz Perc. Journal of the Royal Society Interface, 2014

505 citations recorded by the source corpus.

The Matthew effect describes the phenomenon that in societies, the rich tend to get richer and the potent even more powerful. It is closely related to the concept of preferential attachment in network science, where the more connected nodes are destined to acquire many more links in the future than the auxiliary nodes. Cumulative advantage and success-breads-success also both describe the fact that advantage tends to beget further advantage. The concept is behind the many power laws and scaling behaviour in empirical data, and it is at the heart of self-organization across social and natural sciences. Here, we review the methodology for measuring preferential attachment in empirical data, as well as the observations of the Matthew effect in patterns of scientific collaboration, socio-technical and biological networks, the propagation of citations, the emergence of scientific progress and impact, career longevity, the evolution of common English words and phrases, as well as in education and brain development. We also discuss whether the Matthew effect is due to chance or optimization, for example related to homophily in social systems or efficacy in technological systems, and we outline possible directions for future research.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/361df482f4c74cb85d0f2fa897a4491fbf53ab6f

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Citations in the corpus

Non-social features of smartphone use are most related to depression, anxiety and problematic smartphone use (2017, background): “The “Rich get richer, poor get poorer” model, or “Matthew Effect” (Merton, 1968) is relevant in this regard (Perc, 2014).”
ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing (2023, background): “This phenomenon can perpetuate existing inequalities in academia (Perc, 2014).”
Irreversibility and complex network behavior of stream flow fluctuations (2016, background): “15 In fact, power law and lognormal decay can result from slightly different multiplicative processes with and without a 16 bounded minimum acting as a lower reflective barrier to the multiplicative model [46], while power law and stretched 17 exponential correspond to linear and sublinear preferent”