Systemic Gendered Citation Imbalance in Computer Science: Evidence from Conferences and Journals

2026-03-24

AI Summary

This study investigates whether systematic gender-based citation imbalances exist in computer science conferences and journals. Through large-scale bibliometric analysis—integrating gender inference algorithms, homophily-aware citation modeling, and social network analysis—it reveals, for the first time in this conference-dominated field, that papers with female first or last authors receive significantly fewer citations than expected. The disparity is more pronounced in top-tier conferences than in journals. The research identifies author homophily and prestige as key drivers of this imbalance, underscoring how collaboration network structures influence citation equity. These findings provide empirical evidence of gender bias in scholarly evaluation practices within computer science.

Technology Category

• Computer Vision: Bias, Fairness & Privacy
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning
• 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: Web data provenance, reliability, and authenticity
• 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

Gender imbalance persists across science, technology, engineering, and mathematics (STEM) fields, including computer science, where it appears in researcher demographics, productivity, recognition, hiring, and career progression. Given computer science's rapid expansion and global influence, addressing this imbalance is essential for broadening participation and fueling innovation. Although journal-oriented disciplines exhibit consistent gender imbalances in citation practices, it remains unclear whether similar patterns arise in the conference-centric culture of computer science. Here, we systematically investigate gender imbalance in citations of conference and journal papers in computer science. We find that papers for which a woman is listed as either first or last author receive fewer citations than expected, partly because of homophilic citation tendencies (i.e., authors tend to cite papers that share specific attributes). This imbalance is especially pronounced for conference papers--particularly those published at top-tier venues--relative to journals. Moreover, we find that the prominence of the first or last author and the structure of their local co-authorship networks are potential drivers of these imbalances. By exploring how conference-centric publishing practices can amplify systemic imbalances in computer science, our study offers insights that may inform efforts to foster more equitable representation in academia.

Problem

• gender citation imbalance
• computer science
• conference publishing
• homophilic citation
• authorship gender

Innovation

• gendered citation imbalance
• homophilic citation
• conference-centric publishing
• co-authorship networks
• systemic bias