Ming Tang
- Statistical and Nonlinear Physics top 0.1%
- Computer Networks and Communications top 1%
- Modeling and Simulation top 0.2%
- Sociology and Political Science top 5%
- Public Health, Environmental and Occupational Health top 5%
- Co-authors
- Wei WangYounghae DoZonghua LiuYing‐Cheng LaiTao ZhouYing LiuH. Eugene StanleyLidia A. Braunstein
- Topics
- Complex Network Analysis Techniques (95 papers)Opinion Dynamics and Social Influence (83 papers)COVID-19 epidemiological studies (22 papers)
- Cited by
- Statistical and Nonlinear PhysicsModeling and SimulationComputer Networks and Communications
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaPLoS ONE
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Ming Tang
133 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Statistical and Nonlinear Physics 2.9k
- Computer Networks and Communications 871
- Modeling and Simulation 732
- Sociology and Political Science 507
- Public Health, Environmental and Occupational Health 449
Countries citing papers authored by Ming Tang
This map shows the geographic impact of Ming Tang'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 Ming Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Tang more than expected).
Fields of papers citing papers by Ming Tang
This network shows the impact of papers produced by Ming Tang. 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 Ming Tang. The network helps show where Ming Tang may publish in the future.
Co-authorship network of co-authors of Ming Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Ming Tang. A scholar is included among the top collaborators of Ming Tang 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 Ming Tang. Ming Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 25 | |
| 6 | 4 | |
| 7 | 4 | |
| 8 | 8 | |
| 9 | 5 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 13 | |
| 13 | 16 | |
| 14 | 12 | |
| 15 | 15 | |
| 16 | 43 | |
| 17 | 8 | |
| 18 | Well stability analysis of underbalanced horizontal well in Daniudi gas field | 0 |
| 19 | The Model of the Cementing Matrix Powder Group Fractal Geometry Denseness Effect | 4 |
| 20 | Discussion High Functional Concrete Material | 2 |
About Ming Tang
Ming Tang is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation and Computer Networks and Communications, having authored 146 papers that have together received 3.7k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (95 papers), Opinion Dynamics and Social Influence (83 papers) and COVID-19 epidemiological studies (22 papers). The work is most often cited by research in Statistical and Nonlinear Physics (2.9k citations), Modeling and Simulation (732 citations) and Computer Networks and Communications (871 citations). Ming Tang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Wei Wang, Younghae Do, Zonghua Liu, Ying‐Cheng Lai, Tao Zhou, Ying Liu, H. Eugene Stanley, Lidia A. Braunstein, Haifeng Zhang and P. M. Hui. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.
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.