Yuval Kalish
- Sociology and Political Science top 2%
- Statistical and Nonlinear Physics top 1%
- Social Psychology top 5%
- Neurology top 5%
- Communication top 2%
- Co-authors
- Garry RobinsPhilippa PattisonDean LusherGil LuriaHadas Stiebel‐KalishAlejandro BerensteinMark J. KupersmithMina Westman
- Topics
- Complex Network Analysis Techniques (7 papers)Cultural Differences and Values (4 papers)Social and Intergroup Psychology (3 papers)
- Cited by
- Statistical and Nonlinear PhysicsCommunicationOrganizational Behavior and Human Resource Management
- Partner nations
- IsraelAustraliaUnited States
In The Last Decade
Yuval Kalish
25 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Sociology and Political Science 631
- Statistical and Nonlinear Physics 567
- Social Psychology 237
- Neurology 219
- Communication 211
Countries citing papers authored by Yuval Kalish
This map shows the geographic impact of Yuval Kalish'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 Yuval Kalish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuval Kalish more than expected).
Fields of papers citing papers by Yuval Kalish
This network shows the impact of papers produced by Yuval Kalish. 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 Yuval Kalish. The network helps show where Yuval Kalish may publish in the future.
Co-authorship network of co-authors of Yuval Kalish
This figure shows the co-authorship network connecting the top 25 collaborators of Yuval Kalish. A scholar is included among the top collaborators of Yuval Kalish 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 Yuval Kalish. Yuval Kalish is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 3 | |
| 3 | 5 | |
| 4 | 23 | |
| 5 | 44 | |
| 6 | 19 | |
| 7 | 43 | |
| 8 | 49 | |
| 9 | Making Science: New Generations of Collaborative Knowledge Production | 1 |
| 10 | 20 | |
| 11 | 20 | |
| 12 | 21 | |
| 13 | 12 | |
| 14 | 26 | |
| 15 | 44 | |
| 16 | 86 | |
| 17 | 266 | |
| 18 | 20 | |
| 19 | 62 | |
| 20 | 14 |
About Yuval Kalish
Yuval Kalish is a scholar working on Statistical and Nonlinear Physics, Social Psychology and Neurology, having authored 25 papers that have together received 2.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Cultural Differences and Values (4 papers) and Social and Intergroup Psychology (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (567 citations), Communication (211 citations) and Organizational Behavior and Human Resource Management (156 citations). Yuval Kalish has collaborated with scholars based in Israel, Australia and United States. Frequent co-authors include Garry Robins, Philippa Pattison, Dean Lusher, Gil Luria, Hadas Stiebel‐Kalish, Alejandro Berenstein, Mark J. Kupersmith, Mina Westman, Sharon Toker and Yasunari Niimi. Their work appears in journals such as Journal of Applied Psychology, Neurology and Ophthalmology.
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.