Shuo Yu
Impact in
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- Complex Network Analysis Techniques
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- scientometrics and bibliometrics research
Papers in
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- Advanced Graph Neural Networks 29
- Topic Modeling 10
- Anomaly Detection Techniques and Applications 5
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- Complex Network Analysis Techniques 31
- Co-authors
- Xiangjie Kong (7 shared papers)Feng Xia (24 shared papers)Jiaying Liu (4 shared papers)Wei Wang (8 shared papers)Ivan Lee (9 shared papers)Teshome Megersa Bekele (4 shared papers)Bo Xu (5 shared papers)Xiaomei Bai (4 shared papers)
- Journals
- IEEE Transactions on Computational Social Systems (7 papers)Journal of Network and Computer Applications (2 papers)IEEE Access (2 papers)PeerJ Computer Science (2 papers)IEEE Transactions on Consumer Electronics (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Shuo Yu
80 papers receiving 973 citations
Peers
Comparison fields: 5 of 112
- Statistical and Nonlinear Physics 315
- Statistics, Probability and Uncertainty 122
- Artificial Intelligence 465
- Information Systems 290
- Computer Science Applications 47
Countries citing papers authored by Shuo Yu
This map shows the geographic impact of Shuo Yu'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 Shuo Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuo Yu more than expected).
Fields of papers citing papers by Shuo Yu
This network shows the impact of papers produced by Shuo Yu. 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 Shuo Yu. The network helps show where Shuo Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shuo Yu, 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 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 140 | |
| 2 | 2017 | 70 | |
| 3 | 2017 | 53 | |
| 4 | 2020 | 41 | |
| 5 | 2016 | 36 | |
| 6 | 2021 | 34 | |
| 7 | 2021 | 30 | |
| 8 | 2019 | 29 | |
| 9 | 2021 | 29 | |
| 10 | 2020 | 25 | |
| 11 | 2019 | 24 | |
| 12 | 2016 | 23 | |
| 13 | 2023 | 22 | |
| 14 | 2016 | 21 | |
| 15 | 2023 | 21 | |
| 16 | 2019 | 20 | |
| 17 | 2019 | 19 | |
| 18 | 2017 | 18 | |
| 19 | 2022 | 18 | |
| 20 | 2019 | 18 |
About Shuo Yu
Shuo Yu is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Molecular Biology and Statistics, Probability and Uncertainty, having authored 88 papers that have together received 997 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (31 papers), Advanced Graph Neural Networks (29 papers), Bioinformatics and Genomic Networks (15 papers), scientometrics and bibliometrics research (11 papers), Topic Modeling (10 papers), Recommender Systems and Techniques (10 papers), Anomaly Detection Techniques and Applications (5 papers) and Network Security and Intrusion Detection (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (315 citations), Statistics, Probability and Uncertainty (122 citations), Artificial Intelligence (465 citations), Information Systems (290 citations) and Computer Science Applications (47 citations). Shuo Yu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Xiangjie Kong, Feng Xia, Jiaying Liu, Wei Wang, Ivan Lee, Teshome Megersa Bekele, Bo Xu, Xiaomei Bai, Amr Tolba and Huizhen Jiang. Their work appears in journals such as IEEE Transactions on Computational Social Systems, Journal of Network and Computer Applications, IEEE Access, PeerJ Computer Science and IEEE Transactions on Consumer Electronics.
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.