Aaron Clauset: h-index, Total Citations, and Citation Map
Aaron Clauset's h-index is 55 (91 i10-index, 44,979+ total citations across 4+ publications) according to Google Scholar as of May 2026. Aaron Clauset is affiliated with Professor of Computer Science & BioFrontiers Institute, University of Colorado Boulder.
Aaron Clauset is a researcher affiliated with Professor of Computer Science & BioFrontiers Institute, University of Colorado Boulder, specializing in Network Science, Science of Science, Machine Learning. Their work has been cited 44,979 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Aaron Clauset's Citation Metrics
Bibliometric impact based on 4 indexed publications. Of these, 2 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 55
- i10-Index
- 91
- Total Citations
- 44,979
- Citing Countries
- 21
As of May 2026.
Aaron Clauset has an h-index of 55 and 44,979 total citations across 4 publications, with research cited by institutions in 21 countries.
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Global Impact Map
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Top Cited Works
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Power-law distributions in empirical data
200912,867
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Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher developed a seminal method for identifying community structure in very large networks, establishing a foundational approach for analyzing complex systems in statistical physics.
The researcher developed a hierarchical framework for predicting missing links in complex networks, establishing a foundational method for network structure analysis.
The researcher established a foundational framework for analyzing power-law distributions in empirical data, providing a critical reference for statistical methodology across diverse scientific disciplines.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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