Kaize Shi
Impact in
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- Online Learning and Analytics
- Artificial Intelligence top 10%
- Topic Modeling
- Advanced Graph Neural Networks
- Sentiment Analysis and Opinion Mining
Papers in
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- Topic Modeling 10
- Advanced Graph Neural Networks 5
- Advanced Text Analysis Techniques 4
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- Public Relations and Crisis Communication 5
- Co-authors
- Zhendong Niu (21 shared papers)Hao Lü (14 shared papers)Yifan Zhu (15 shared papers)Qika Lin (4 shared papers)Yisheng Lv (3 shared papers)Xueping Peng (5 shared papers)Shanshan Wan (1 shared paper)Qi Zhang (3 shared papers)
- Journals
- IEEE Transactions on Computational Social Systems (6 papers)Knowledge-Based Systems (3 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)Neurocomputing (2 papers)Future Generation Computer Systems (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Kaize Shi
26 papers receiving 413 citations
Peers
Comparison fields: 5 of 72
- Computer Science Applications 65
- Artificial Intelligence 233
- Information Systems 132
- Transportation 24
- Communication 25
Countries citing papers authored by Kaize Shi
This map shows the geographic impact of Kaize Shi'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 Kaize Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaize Shi more than expected).
Fields of papers citing papers by Kaize Shi
This network shows the impact of papers produced by Kaize Shi. 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 Kaize Shi. The network helps show where Kaize Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Kaize Shi, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 73 | |
| 2 | 2021 | 53 | |
| 3 | 2021 | 37 | |
| 4 | 2021 | 28 | |
| 5 | 2022 | 27 | |
| 6 | 2018 | 25 | |
| 7 | 2019 | 24 | |
| 8 | 2019 | 24 | |
| 9 | 2020 | 24 | |
| 10 | 2018 | 16 | |
| 11 | 2024 | 16 | |
| 12 | 2021 | 15 | |
| 13 | 2019 | 15 | |
| 14 | 2020 | 8 | |
| 15 | 2024 | 7 | |
| 16 | 2023 | 5 | |
| 17 | 2018 | 5 | |
| 18 | 2019 | 4 | |
| 19 | 2024 | 4 | |
| 20 | 2024 | 3 |
About Kaize Shi
Kaize Shi is a scholar working on Artificial Intelligence, Communication, Information Systems, Statistical and Nonlinear Physics and Building and Construction, having authored 39 papers that have together received 423 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Traffic Prediction and Management Techniques (6 papers), Recommender Systems and Techniques (6 papers), Complex Network Analysis Techniques (6 papers), Public Relations and Crisis Communication (5 papers), Advanced Graph Neural Networks (5 papers), Human Mobility and Location-Based Analysis (4 papers) and Advanced Text Analysis Techniques (4 papers). The work is most often cited by research in Computer Science Applications (65 citations), Artificial Intelligence (233 citations), Information Systems (132 citations), Transportation (24 citations) and Communication (25 citations). Kaize Shi has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Zhendong Niu, Hao Lü, Yifan Zhu, Qika Lin, Yisheng Lv, Xueping Peng, Shanshan Wan, Qi Zhang, Yusen Wang and Hui He. Their work appears in journals such as IEEE Transactions on Computational Social Systems, Knowledge-Based Systems, IEEE Transactions on Knowledge and Data Engineering, Neurocomputing and Future Generation Computer Systems.
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.