Bin Zhou
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Sentiment Analysis and Opinion Mining
Papers in
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- Advanced Text Analysis Techniques 13
- Topic Modeling 12
- Advanced Graph Neural Networks 11
- Sentiment Analysis and Opinion Mining 10
-
- Complex Network Analysis Techniques 35
- Opinion Dynamics and Social Influence 12
- Co-authors
- Yan Jia (25 shared papers)Quanyuan Wu (8 shared papers)Fazhi Yan (5 shared papers)Yi Han (11 shared papers)Shoujian Peng (6 shared papers)Ye Wang (4 shared papers)Shudong Li (4 shared papers)Aiping Li (5 shared papers)
- Journals
- World Wide Web (3 papers)Nonlinear Dynamics (3 papers)Neurocomputing (2 papers)IEEE Access (2 papers)Natural Resources Research (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Bin Zhou
90 papers receiving 740 citations
Peers
Comparison fields: 5 of 93
- Statistical and Nonlinear Physics 191
- Artificial Intelligence 315
- Information Systems 202
- Ocean Engineering 131
- Safety, Risk, Reliability and Quality 44
Countries citing papers authored by Bin Zhou
This map shows the geographic impact of Bin Zhou'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 Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Zhou more than expected).
Fields of papers citing papers by Bin Zhou
This network shows the impact of papers produced by Bin Zhou. 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 Zhou. The network helps show where Bin Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Zhou, 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 102 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 71 | |
| 2 | 2017 | 56 | |
| 3 | 2020 | 35 | |
| 4 | 2019 | 34 | |
| 5 | 2018 | 33 | |
| 6 | 2009 | 30 | |
| 7 | 2019 | 30 | |
| 8 | 2013 | 23 | |
| 9 | 2017 | 20 | |
| 10 | 2008 | 20 | |
| 11 | 2015 | 18 | |
| 12 | 2017 | 18 | |
| 13 | 2007 | 18 | |
| 14 | 2022 | 17 | |
| 15 | 2014 | 16 | |
| 16 | 2017 | 16 | |
| 17 | 2013 | 16 | |
| 18 | 2015 | 15 | |
| 19 | 2017 | 13 | |
| 20 | 2022 | 12 |
About Bin Zhou
Bin Zhou is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Computer Networks and Communications and Control and Systems Engineering, having authored 102 papers that have together received 761 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (35 papers), Advanced Text Analysis Techniques (13 papers), Topic Modeling (12 papers), Opinion Dynamics and Social Influence (12 papers), Web Data Mining and Analysis (11 papers), Advanced Graph Neural Networks (11 papers), Spam and Phishing Detection (10 papers) and Sentiment Analysis and Opinion Mining (10 papers). The work is most often cited by research in Statistical and Nonlinear Physics (191 citations), Artificial Intelligence (315 citations), Information Systems (202 citations), Ocean Engineering (131 citations) and Safety, Risk, Reliability and Quality (44 citations). Bin Zhou has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yan Jia, Quanyuan Wu, Fazhi Yan, Yi Han, Shoujian Peng, Ye Wang, Shudong Li, Aiping Li, Zhu Xiang and Hua Wang. Their work appears in journals such as World Wide Web, Nonlinear Dynamics, Neurocomputing, IEEE Access and Natural Resources Research.
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.