Bin Wu
Impact in
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Safety Research top 1%
- Experimental Behavioral Economics Studies
Papers in
-
- Complex Network Analysis Techniques 93
- Opinion Dynamics and Social Influence 48
-
- Advanced Graph Neural Networks 34
- Topic Modeling 17
- Co-authors
- Arne Traulsen (13 shared papers)Long Wang (17 shared papers)Chuan Shi (19 shared papers)Philip S. Yu (8 shared papers)Chenguang Song (11 shared papers)Bai Wang (29 shared papers)Jinming Du (7 shared papers)Philipp M. Altrock (2 shared papers)
- Journals
- Neurocomputing (5 papers)Scientific Reports (4 papers)Applied Optics (4 papers)Physical review. E (4 papers)Journal of The Royal Society Interface (4 papers)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Bin Wu
223 papers receiving 4.0k citations
Peers
Comparison fields: 5 of 135
- Statistical and Nonlinear Physics 1.2k
- Safety Research 423
- Artificial Intelligence 1.3k
- Sociology and Political Science 1.7k
- Information Systems 883
Countries citing papers authored by Bin Wu
This map shows the geographic impact of Bin Wu'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 Bin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Wu more than expected).
Fields of papers citing papers by Bin Wu
This network shows the impact of papers produced by Bin Wu. 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 Bin Wu. The network helps show where Bin Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Wu, 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 243 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 216 | |
| 2 | 2015 | 193 | |
| 3 | 2020 | 164 | |
| 4 | 2010 | 150 | |
| 5 | 2014 | 137 | |
| 6 | 2010 | 130 | |
| 7 | 2007 | 126 | |
| 8 | 2014 | 109 | |
| 9 | 2013 | 102 | |
| 10 | 2021 | 101 | |
| 11 | 2011 | 92 | |
| 12 | 2012 | 78 | |
| 13 | 2012 | 78 | |
| 14 | 2012 | 77 | |
| 15 | 2013 | 77 | |
| 16 | 2014 | 76 | |
| 17 | 2015 | 61 | |
| 18 | 2015 | 57 | |
| 19 | 2010 | 56 | |
| 20 | 2013 | 56 |
About Bin Wu
Bin Wu is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science and Information Systems, having authored 243 papers that have together received 4.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (93 papers), Opinion Dynamics and Social Influence (48 papers), Evolutionary Game Theory and Cooperation (42 papers), Advanced Graph Neural Networks (34 papers), Evolution and Genetic Dynamics (28 papers), Topic Modeling (17 papers), Optical measurement and interference techniques (17 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (14 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.2k citations), Safety Research (423 citations), Artificial Intelligence (1.3k citations), Sociology and Political Science (1.7k citations) and Information Systems (883 citations). Bin Wu has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Arne Traulsen, Long Wang, Chuan Shi, Philip S. Yu, Chenguang Song, Bai Wang, Jinming Du, Philipp M. Altrock, Xiangnan Kong and Nianwen Ning. Their work appears in journals such as Neurocomputing, Scientific Reports, Applied Optics, Physical review. E and Journal of The Royal Society Interface.
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.