Ying Ding
-
- scientometrics and bibliometrics research 45
- Health Informatics top 0.5%
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques 45
- Information Systems top 0.2%
- Service-Oriented Architecture and Web Services 21
- Artificial Intelligence top 0.5%
- Semantic Web and Ontologies 40
- Advanced Text Analysis Techniques 26
- Topic Modeling 24
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- Biomedical Text Mining and Ontologies 31
- Bioinformatics and Genomic Networks 22
- Co-authors
- Erjia YanSchubert FooDietmar WolframRonald RousseauGobinda ChowdhuryBlaise CroninDavid WildCassidy R. Sugimoto
- Journals
- Journal of Informetrics (17 papers)Journal of the Association for Information Science and Technology (12 papers)Scientometrics (9 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Ying Ding
359 papers receiving 10.1k citations
Hit Papers
Peers
Comparison fields: 5 of 232
- Statistics, Probability and Uncertainty 1.4k
- Health Informatics 181
- Statistical and Nonlinear Physics 1.4k
- Information Systems 2.1k
- Artificial Intelligence 2.5k
Countries citing papers authored by Ying Ding
This map shows the geographic impact of Ying Ding'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 Ying Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Ding more than expected).
Fields of papers citing papers by Ying Ding
This network shows the impact of papers produced by Ying Ding. 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 Ying Ding. The network helps show where Ying Ding may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying Ding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 2 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 12 | |
| 14 | 2021 | 29 | |
| 15 | 2020 | 42 | |
| 16 | 2019 | 68 | |
| 17 | 2010 | 67 | |
| 18 | Optimizing semantic Web services ranking using parallelization and rank aggregation techniques | 2010 | 0 |
| 19 | Monte Carlo Simulation of Beam Wander in Atmospheric Turbulence Based on Spherical-Bubble Model | 2008 | 1 |
| 20 | Transnet Architecture and Logistical Networking for Distributed Storage. | 2004 | 2 |
About Ying Ding
Ying Ding is a scholar working on Statistics, Probability and Uncertainty, Health Informatics and Artificial Intelligence, having authored 392 papers that have together received 10.6k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (45 papers), scientometrics and bibliometrics research (45 papers), Semantic Web and Ontologies (40 papers), Biomedical Text Mining and Ontologies (31 papers), Advanced Text Analysis Techniques (26 papers), Topic Modeling (24 papers), Bioinformatics and Genomic Networks (22 papers) and Service-Oriented Architecture and Web Services (21 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (1.4k citations), Health Informatics (181 citations) and Statistical and Nonlinear Physics (1.4k citations). Ying Ding has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Erjia Yan, Schubert Foo, Dietmar Wolfram, Ronald Rousseau, Gobinda Chowdhury, Blaise Cronin, David Wild, Cassidy R. Sugimoto, Dieter Fensel and Yi Bu. Their work appears in journals such as Journal of Informetrics, Journal of the Association for Information Science and Technology, Scientometrics, Information Processing & Management and Journal of Information Science.
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.