Alec Kirkley: h-index, Total Citations, and Citation Map
Alec Kirkley's h-index is 15 (20 i10-index, 1,009+ total citations across 4+ publications) according to Google Scholar as of May 2026. Alec Kirkley is affiliated with University of Hong Kong.
Alec Kirkley is a researcher affiliated with University of Hong Kong, specializing in Statistical Physics, Network Science, Statistical Inference. Their work has been cited 1,009 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Alec Kirkley's Citation Metrics
Bibliometric impact based on 4 indexed publications.
- H-Index
- 15
- i10-Index
- 20
- Total Citations
- 1,009
- Citing Countries
- 13
As of May 2026.
Alec Kirkley has an h-index of 15 and 1,009 total citations across 4 publications, with research cited by institutions in 13 countries.
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Global Impact Map
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Top Cited Works
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From the betweenness centrality in street networks to structural invariants in random planar graphs
2018222
Top Citing Countries
Top Citing Institutions
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 established a theoretical bridge between street network betweenness centrality and structural invariants in random planar graphs, a contribution validated by high independent citation rates.
The researcher advanced the theoretical understanding of structural balance in signed networks through a seminal 2019 publication that has garnered significant independent scholarly attention.
The researcher advanced the quantitative analysis of interdisciplinary collaboration by characterizing mixing patterns in co-authorship networks across multiple scales.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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