Jacob G. Foster
- Statistical and Nonlinear Physics top 2%
- Statistics, Probability and Uncertainty top 1%
- Sociology and Political Science top 10%
- Molecular Biology
- Artificial Intelligence top 10%
- Co-authors
- James A. EvansAndrey RzhetskyDavid FosterMaya PaczuskiPeter GrassbergerIan FosterFeng ShiAlina Arseniev‐Koehler
- Topics
- Complex Network Analysis Techniques (8 papers)Bioinformatics and Genomic Networks (7 papers)Computational and Text Analysis Methods (4 papers)
- Cited by
- Statistics, Probability and UncertaintyStatistical and Nonlinear PhysicsGeneral Social Sciences
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jacob G. Foster
29 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Statistical and Nonlinear Physics 310
- Statistics, Probability and Uncertainty 254
- Sociology and Political Science 194
- Molecular Biology 168
- Artificial Intelligence 149
Countries citing papers authored by Jacob G. Foster
This map shows the geographic impact of Jacob G. Foster's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jacob G. Foster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob G. Foster more than expected).
Fields of papers citing papers by Jacob G. Foster
This network shows the impact of papers produced by Jacob G. Foster. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jacob G. Foster. The network helps show where Jacob G. Foster may publish in the future.
Co-authorship network of co-authors of Jacob G. Foster
This figure shows the co-authorship network connecting the top 25 collaborators of Jacob G. Foster. A scholar is included among the top collaborators of Jacob G. Foster based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jacob G. Foster. Jacob G. Foster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 36 | |
| 5 | 4 | |
| 6 | 23 | |
| 7 | 14 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | 19 | |
| 11 | 79 | |
| 12 | 5 | |
| 13 | 1 | |
| 14 | 37 | |
| 15 | 20 | |
| 16 | 1 | |
| 17 | 174 | |
| 18 | 37 | |
| 19 | 13 | |
| 20 | Fostering Teacher Learning in Systemic Reform: A Design Proposal for Developing Professional Development. | 14 |
About Jacob G. Foster
Jacob G. Foster is a scholar working on General Social Sciences, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty, having authored 29 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Bioinformatics and Genomic Networks (7 papers) and Computational and Text Analysis Methods (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (254 citations), Statistical and Nonlinear Physics (310 citations) and General Social Sciences (66 citations). Jacob G. Foster has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include James A. Evans, Andrey Rzhetsky, David Foster, Maya Paczuski, Peter Grassberger, Ian Foster, Feng Shi, Alina Arseniev‐Koehler, Jevin D. West and Carl T. Bergstrom. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and American Sociological Review.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.