Gui Guan
Impact in
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- Opinion Dynamics and Social Influence
- Complex Network Analysis Techniques
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
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- Opinion Dynamics and Social Influence 8
- Complex Network Analysis Techniques 5
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- Mathematical and Theoretical Epidemiology and Ecology Models 6
- Co-authors
- Linhe Zhu (7 shared papers)Yimin Li (1 shared paper)Zhenyuan Guo (3 shared papers)Shuling Shen (3 shared papers)Zhengdi Zhang (2 shared papers)Fan Yang (1 shared paper)Yanyu Xiao (1 shared paper)
- Journals
- Communications in Nonlinear Science and Numerical Simulation (2 papers)Applied Mathematical Modelling (2 papers)Physica A Statistical Mechanics and its Applications (1 paper)Information Sciences (1 paper)Journal of Mathematical Analysis and Applications (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Gui Guan
10 papers receiving 354 citations
Peers
Comparison fields: 5 of 42
- Statistical and Nonlinear Physics 261
- Modeling and Simulation 91
- Public Health, Environmental and Occupational Health 164
- Genetics 58
- Computer Networks and Communications 51
Countries citing papers authored by Gui Guan
This map shows the geographic impact of Gui Guan'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 Gui Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gui Guan more than expected).
Fields of papers citing papers by Gui Guan
This network shows the impact of papers produced by Gui Guan. 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 Gui Guan. The network helps show where Gui Guan may publish in the future.
Co-authors
The 7 scholars most cited alongside Gui Guan, 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 | 2019 | 106 | |
| 2 | 2023 | 63 | |
| 3 | 2021 | 59 | |
| 4 | 2019 | 37 | |
| 5 | 2021 | 33 | |
| 6 | 2023 | 22 | |
| 7 | 2021 | 17 | |
| 8 | 2023 | 14 | |
| 9 | 2024 | 7 | |
| 10 | 2020 | 6 |
About Gui Guan
Gui Guan is a scholar working on Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health, Genetics, Modeling and Simulation and Sociology and Political Science, having authored 10 papers that have together received 364 indexed citations. Recurring topics across this work include Opinion Dynamics and Social Influence (8 papers), Mathematical and Theoretical Epidemiology and Ecology Models (6 papers), Complex Network Analysis Techniques (5 papers), Evolution and Genetic Dynamics (4 papers), COVID-19 epidemiological studies (4 papers), Opportunistic and Delay-Tolerant Networks (1 paper), Misinformation and Its Impacts (1 paper) and Evolutionary Game Theory and Cooperation (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (261 citations), Modeling and Simulation (91 citations), Public Health, Environmental and Occupational Health (164 citations), Genetics (58 citations) and Computer Networks and Communications (51 citations). Gui Guan has collaborated with scholars based in China and United States. Frequent co-authors include Linhe Zhu, Yimin Li, Zhenyuan Guo, Shuling Shen, Zhengdi Zhang, Fan Yang and Yanyu Xiao. Their work appears in journals such as Communications in Nonlinear Science and Numerical Simulation, Applied Mathematical Modelling, Physica A Statistical Mechanics and its Applications, Information Sciences and Journal of Mathematical Analysis and Applications.
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.