Per Block
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
-
- Complex Network Analysis Techniques 12
- Opinion Dynamics and Social Influence 9
-
- Mental Health Research Topics 6
- Co-authors
- Melinda Mills (4 shared papers)Jennifer B. Dowd (4 shared papers)Christoph Stadtfeld (9 shared papers)Valentina Rotondi (2 shared papers)David M. Brazel (1 shared paper)Xuejie Ding (1 shared paper)Liliana Andriano (1 shared paper)Thomas Grund (1 shared paper)
- Journals
- Social Networks (5 papers)Network Science (3 papers)Sociological Methodology (3 papers)Scientific Reports (2 papers)Proceedings of the National Academy of Sciences (2 papers)
- Partner nations
- SwitzerlandUnited KingdomNetherlands
In The Last Decade
Per Block
26 papers receiving 1.9k citations
Per Block's Hit Papers
Peers
Comparison fields: 5 of 144
- Modeling and Simulation 522
- Statistical and Nonlinear Physics 368
- Health 128
- Communication 97
- Experimental and Cognitive Psychology 148
Countries citing papers authored by Per Block
This map shows the geographic impact of Per Block'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 Per Block with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Per Block more than expected).
Fields of papers citing papers by Per Block
This network shows the impact of papers produced by Per Block. 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 Per Block. The network helps show where Per Block may publish in the future.
Co-authors
The 25 scholars most cited alongside Per Block, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Demographic science aids in understanding the spread and fatality rates of COVID-19 Hit paper breakdown → | 2020 | 627 |
| 2 | 2020 | 371 | |
| 3 | 2014 | 173 | |
| 4 | 2016 | 146 | |
| 5 | 2014 | 136 | |
| 6 | 2016 | 84 | |
| 7 | 2017 | 74 | |
| 8 | 2017 | 71 | |
| 9 | 2017 | 70 | |
| 10 | 2015 | 44 | |
| 11 | 2018 | 25 | |
| 12 | 2020 | 19 | |
| 13 | 2017 | 19 | |
| 14 | 2020 | 16 | |
| 15 | 2020 | 14 | |
| 16 | 2019 | 14 | |
| 17 | 2018 | 10 | |
| 18 | 2017 | 9 | |
| 19 | 2022 | 9 | |
| 20 | 2023 | 8 |
About Per Block
Per Block is a scholar working on Statistical and Nonlinear Physics, Experimental and Cognitive Psychology, Modeling and Simulation, Sociology and Political Science and Social Psychology, having authored 27 papers that have together received 2.0k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (12 papers), Opinion Dynamics and Social Influence (9 papers), Mental Health Research Topics (6 papers), Evolutionary Game Theory and Cooperation (5 papers), COVID-19 epidemiological studies (4 papers), Social Capital and Networks (4 papers), Neuroendocrine regulation and behavior (3 papers) and Primate Behavior and Ecology (2 papers). The work is most often cited by research in Modeling and Simulation (522 citations), Statistical and Nonlinear Physics (368 citations), Health (128 citations), Communication (97 citations) and Experimental and Cognitive Psychology (148 citations). Per Block has collaborated with scholars based in Switzerland, United Kingdom and Netherlands. Frequent co-authors include Melinda Mills, Jennifer B. Dowd, Christoph Stadtfeld, Valentina Rotondi, David M. Brazel, Xuejie Ding, Liliana Andriano, Thomas Grund, Marion Hoffman and Isabel J. Raabe. Their work appears in journals such as Social Networks, Network Science, Sociological Methodology, Scientific Reports and Proceedings of the National Academy of Sciences.
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.