Purpose: This study investigates factors associated with scientific recognition, examining how collaboration networks influence the path to ACM fellowship.
Design/methodology/approach: We analyzed 1,497 ACM fellows (1994-2023) using linear regression on 286,791 publication records, examining co-authorship patterns and institutional overlaps while controlling for productivity metrics.
Findings: Collaboration with ACM fellows among new electees increased from 43% to over 90%. Collaborating with ACM fellows is associated with achieving fellowship 3.8 years earlier, with frequent, recent collaborations and prestigious collaborators exhibiting even shorter time intervals to recognition. Gender and institutional factors also significantly impact timing.
Research limitations: The study is correlational, focuses on one society, and may not capture all forms of scientific contribution beyond traditional metrics.
Practical implications: Current processes may favor well-connected candidates. Reforms should increase transparency and expand recognition criteria to address biases and promote inclusivity.
Originality/value: This provides the first comprehensive three-decade analysis of ACM fellowship patterns, revealing the growing importance of strategic networking in scientific recognition and offering evidence-based recommendations for more inclusive evaluation processes.
Fan Jiang, Tongxin Pan, Jue Wang, Yifang Ma
. The road to ACM fellowship: Examining collaboration patterns and disparities[J]. Journal of Data and Information Science, 0
: 20250044
-20250044
.
DOI: 10.2478/jdis-2025-0044
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