Xiaobin Rui
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Complex Network Analysis Techniques 18
- Opinion Dynamics and Social Influence 14
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- Advanced Graph Neural Networks 10
- Text and Document Classification Technologies 3
- Co-authors
- Zhixiao Wang (23 shared papers)Guan Yuan (5 shared papers)Chengcheng Sun (7 shared papers)Na Bai (3 shared papers)Xinguang Xiang (1 shared paper)Zechao Li (1 shared paper)Tarik Hadzibeganovic (2 shared papers)Philip S. Yu (7 shared papers)
- Journals
- Computing (4 papers)Knowledge-Based Systems (3 papers)Physica A Statistical Mechanics and its Applications (3 papers)ACM Transactions on Knowledge Discovery from Data (2 papers)IEEE Access (2 papers)
- Partner nations
- ChinaUnited StatesAustria
In The Last Decade
Xiaobin Rui
21 papers receiving 322 citations
Peers
Comparison fields: 5 of 55
- Statistical and Nonlinear Physics 219
- Artificial Intelligence 118
- Modeling and Simulation 12
- Transportation 17
- Computer Networks and Communications 54
Countries citing papers authored by Xiaobin Rui
This map shows the geographic impact of Xiaobin Rui'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 Xiaobin Rui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaobin Rui more than expected).
Fields of papers citing papers by Xiaobin Rui
This network shows the impact of papers produced by Xiaobin Rui. 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 Xiaobin Rui. The network helps show where Xiaobin Rui may publish in the future.
Co-authors
The 22 scholars most cited alongside Xiaobin Rui, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 46 | |
| 2 | 2018 | 40 | |
| 3 | 2023 | 35 | |
| 4 | 2019 | 30 | |
| 5 | 2021 | 28 | |
| 6 | 2022 | 21 | |
| 7 | 2019 | 21 | |
| 8 | 2018 | 17 | |
| 9 | 2020 | 16 | |
| 10 | 2021 | 13 | |
| 11 | 2020 | 12 | |
| 12 | 2022 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2020 | 9 | |
| 15 | 2022 | 9 | |
| 16 | 2022 | 3 | |
| 17 | 2024 | 3 | |
| 18 | 2021 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2022 | 2 |
About Xiaobin Rui
Xiaobin Rui is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Networks and Communications, Sociology and Political Science and Public Health, Environmental and Occupational Health, having authored 24 papers that have together received 329 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (18 papers), Opinion Dynamics and Social Influence (14 papers), Advanced Graph Neural Networks (10 papers), Peer-to-Peer Network Technologies (3 papers), Misinformation and Its Impacts (3 papers), Text and Document Classification Technologies (3 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers) and Network Security and Intrusion Detection (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (219 citations), Artificial Intelligence (118 citations), Modeling and Simulation (12 citations), Transportation (17 citations) and Computer Networks and Communications (54 citations). Xiaobin Rui has collaborated with scholars based in China, United States and Austria. Frequent co-authors include Zhixiao Wang, Guan Yuan, Chengcheng Sun, Na Bai, Xinguang Xiang, Zechao Li, Tarik Hadzibeganovic, Philip S. Yu, Xiaodong Yang and Xiang Lin. Their work appears in journals such as Computing, Knowledge-Based Systems, Physica A Statistical Mechanics and its Applications, ACM Transactions on Knowledge Discovery from Data and IEEE Access.
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.