Emergence of Structural Disparities in the Web of Scientific Citations

2026-01-19

AI Summary

This study addresses the persistent structural inequities in the allocation of scholarly attention within scientific citation networks, which are shaped by gender and institutional prestige. The authors propose a generative model of citation network growth that integrates homophily-driven preferences, preferential attachment, and group size effects to systematically uncover the mechanisms underlying these disparities. Their analysis reveals that merely increasing the representation of underrepresented groups is insufficient to redress imbalance; effective mitigation requires simultaneously reducing homophilic citation biases and enhancing the visibility of their scholarly contributions. By quantifying the distinct impacts of gender and institutional prestige on citation distributions, the work advances a multidimensional intervention framework that offers both theoretical grounding and actionable pathways toward fostering a more equitable, transparent, and inclusive scientific communication ecosystem.

Technology Category

• Knowledge Representation and Reasoning: Preferences
• Reasoning under Uncertainty: Causality
• Application Domains: Humanities & Computational Social Science

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Web Mining and Content Analysis: Models for Web evolution
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs

Abstract

Scientific attention is unevenly distributed, creating inequities in recognition and distorting access to opportunities. Using citations as a proxy, we quantify disparities in attention by gender and institutional prestige. We find that women receive systematically fewer citations than men, and that attention is increasingly concentrated among authors from elite institutions -- patterns not fully explained by underrepresentation alone. To explain these dynamics, we introduce a model of citation network growth that incorporates homophily (tendency to cite similar authors), preferential attachment (favoring highly cited authors) and group size (underrepresentation). The model shows that disparities arise not only from group size imbalances but also from cumulative advantage amplifying biased citation preferences. Importantly, increasing representation alone is often insufficient to reduce disparities. Effective strategies should also include reducing homophily, amplifying the visibility of underrepresented groups, and supporting equitable integration of newcomers. Our findings highlight the challenges of mitigating inequities in asymmetric networks like citations, where recognition flows in one direction. By making visible the mechanisms through which attention is distributed, we contribute to efforts toward a more responsible web of science that is fairer, more transparent, and more inclusive, and that better sustains innovation and knowledge production.

Problem

• citation disparities
• gender inequality
• institutional prestige
• structural inequity
• scientific attention

Innovation

• citation network
• homophily
• preferential attachment
• structural inequality
• cumulative advantage