Mark E. Dickison
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
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- Complex Network Analysis Techniques 6
- Opinion Dynamics and Social Influence 5
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- Network Security and Intrusion Detection 1
- Peer-to-Peer Network Technologies 1
- Co-authors
- H. Eugene Stanley (2 shared papers)S. Havlin (2 shared papers)Matteo Magnani (3 shared papers)Luca Rossi (3 shared papers)Thomas Vojta (1 shared paper)Federico Vázquez (1 shared paper)P. A. Macri (1 shared paper)Shlomo Havlin (1 shared paper)
- Journals
- Europhysics Letters (EPL) (1 paper)OpenBU (Boston University) (1 paper)Cambridge University Press eBooks (3 papers)Physical Review E (3 papers)
- Partner nations
- United StatesSwedenIsrael
In The Last Decade
Mark E. Dickison
6 papers receiving 512 citations
Peers
Comparison fields: 5 of 83
- Statistical and Nonlinear Physics 374
- Modeling and Simulation 82
- Condensed Matter Physics 91
- Mathematical Physics 56
- Computer Networks and Communications 67
Countries citing papers authored by Mark E. Dickison
This map shows the geographic impact of Mark E. Dickison'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 Mark E. Dickison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark E. Dickison more than expected).
Fields of papers citing papers by Mark E. Dickison
This network shows the impact of papers produced by Mark E. Dickison. 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 Mark E. Dickison. The network helps show where Mark E. Dickison may publish in the future.
Co-authors
The 10 scholars most cited alongside Mark E. Dickison, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 208 | |
| 2 | 2016 | 135 | |
| 3 | 2005 | 87 | |
| 4 | 2011 | 60 | |
| 5 | 2010 | 31 | |
| 6 | 2016 | 4 | |
| 7 | 2016 | 1 | |
| 8 | DYNAMIC AND INTERACTING COMPLEX NETWORKS | 2012 | 1 |
About Mark E. Dickison
Mark E. Dickison is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Mathematical Physics, Modeling and Simulation and Condensed Matter Physics, having authored 8 papers that have together received 527 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (6 papers), Opinion Dynamics and Social Influence (5 papers), COVID-19 epidemiological studies (2 papers), Stochastic processes and statistical mechanics (2 papers), Network Security and Intrusion Detection (1 paper), Peer-to-Peer Network Technologies (1 paper) and Theoretical and Computational Physics (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (374 citations), Modeling and Simulation (82 citations), Condensed Matter Physics (91 citations), Mathematical Physics (56 citations) and Computer Networks and Communications (67 citations). Mark E. Dickison has collaborated with scholars based in United States, Sweden and Israel. Frequent co-authors include H. Eugene Stanley, S. Havlin, Matteo Magnani, Luca Rossi, Thomas Vojta, Federico Vázquez, P. A. Macri, Shlomo Havlin, Roni Parshani and Reuven Cohen. Their work appears in journals such as Europhysics Letters (EPL), OpenBU (Boston University), Cambridge University Press eBooks and Physical Review E.
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.