Ying Sha
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
- Sentiment Analysis and Opinion Mining
Papers in
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- Topic Modeling 9
- Sentiment Analysis and Opinion Mining 6
- Advanced Graph Neural Networks 5
- Advanced Text Analysis Techniques 4
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- Complex Network Analysis Techniques 11
- Opinion Dynamics and Social Influence 4
- Co-authors
- Huan Wang (2 shared papers)Lei Fang (2 shared papers)Bo Jiang (2 shared papers)Xiaofei Zhou (3 shared papers)Qi Liang (1 shared paper)Changjian Wang (1 shared paper)Zeliang Song (1 shared paper)Lihong V. Wang (1 shared paper)
- Journals
- ACM Transactions on the Web (1 paper)Applied Sciences (1 paper)Human Molecular Genetics (1 paper)Knowledge-Based Systems (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)
- Partner nations
- ChinaUnited KingdomAustralia
In The Last Decade
Ying Sha
26 papers receiving 167 citations
Peers
Comparison fields: 5 of 48
- Statistical and Nonlinear Physics 65
- Artificial Intelligence 115
- Information Systems 47
- Computer Networks and Communications 20
- Communication 6
Countries citing papers authored by Ying Sha
This map shows the geographic impact of Ying Sha'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 Sha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Sha more than expected).
Fields of papers citing papers by Ying Sha
This network shows the impact of papers produced by Ying Sha. 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 Sha. The network helps show where Ying Sha may publish in the future.
Co-authors
The 25 scholars most cited alongside Ying Sha, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 60 | |
| 2 | 2022 | 19 | |
| 3 | 2016 | 13 | |
| 4 | 2015 | 13 | |
| 5 | 2015 | 13 | |
| 6 | 2021 | 6 | |
| 7 | 2020 | 6 | |
| 8 | 2019 | 6 | |
| 9 | 2024 | 3 | |
| 10 | 2022 | 3 | |
| 11 | 2024 | 3 | |
| 12 | 2019 | 3 | |
| 13 | 2013 | 3 | |
| 14 | 2017 | 2 | |
| 15 | 2021 | 2 | |
| 16 | 2022 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2013 | 2 |
About Ying Sha
Ying Sha is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Sociology and Political Science and Signal Processing, having authored 30 papers that have together received 171 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (11 papers), Topic Modeling (9 papers), Misinformation and Its Impacts (7 papers), Spam and Phishing Detection (6 papers), Sentiment Analysis and Opinion Mining (6 papers), Advanced Graph Neural Networks (5 papers), Advanced Text Analysis Techniques (4 papers) and Opinion Dynamics and Social Influence (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (65 citations), Artificial Intelligence (115 citations), Information Systems (47 citations), Computer Networks and Communications (20 citations) and Communication (6 citations). Ying Sha has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Huan Wang, Lei Fang, Bo Jiang, Xiaofei Zhou, Qi Liang, Changjian Wang, Zeliang Song, Lihong V. Wang, Shirui Pan and Zhi Zeng. Their work appears in journals such as ACM Transactions on the Web, Applied Sciences, Human Molecular Genetics, Knowledge-Based Systems and IEEE Transactions on Knowledge and Data Engineering.
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.