Reproduce “Co-citation and Co-authorship Networks of Statisticians” on OpenResearch
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About this paper
Pengsheng Ji, Jiashun Jin, Zheng Tracy Ke, Wanshan Li
Ji et al. developed and publicly released MADStat, a comprehensive dataset of 83,331 papers and 47,311 authors in statistics from 1975-2015, demonstrating modern statistical tools to analyze research interests and community structures. The analysis revealed a "statistics triangle" of primary research areas and a 4-layer hierarchical community tree with 26 leaf communities, illustrating the dynamic evolution of the field.
Key insights
- The statistics discipline exhibits a "statistics triangle" of primary research areas (Bayes, Biostatistics, Nonparametric) and 15 sub-areas, with biostatistics and high-dimensional data analysis showing increased popularity over time.
- Research interests and community affiliations within statistics are dynamic, with authors demonstrating varied trajectories and shifts in focus influenced by shared interests, geography, academic genealogy, and institutional ties.
- Statisticians' co-authorship diversity, as measured by personalized network analysis, may be lower than expected, with approximately 80% of prolific authors tending to form single, tight-knit collaboration groups.
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