The road to ACM fellowship: Examining collaboration patterns and disparities

ABSTRACT 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 evidencebased recommendations for more inclusive evaluation processes.

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Publication Details

Journal
Journal of Data and Information Science
Published
2025-06-22
DOI
https://doi.org/10.2478/jdis-2025-0044
Citations
1
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
1.40
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article

The road to ACM fellowship: Examining collaboration patterns and disparities

Fan Jiang, Jue Wang, Yifang Ma, Tongxin Pan
1 citations
Journal of Data and Information Science
scientometrics and bibliometrics research
1.40
article

The road to ACM fellowship: Examining collaboration patterns and disparities

Fan Jiang, Jue Wang, Yifang Ma, Tongxin Pan
article en
1 citations

Abstract

ABSTRACT 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 evidencebased recommendations for more inclusive evaluation processes.

Journal of Data and Information ScienceVol. 10(4)
Nanyang Technological University (SG), Southern University of Science and Technology (CN)
Openalex Percentile: Top 14%
scientometrics and bibliometrics research
1.40
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The road to ACM fellowship: Examining collaboration patterns and disparities — Fan Jiang, Jue Wang, et al. · Journal of Data and Information Science (2025) | TGRS Research Map | TGRS