Dehong Ma
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
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- Mosquito-borne diseases and control
Papers in
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- Mosquito-borne diseases and control 13
- Malaria Research and Control 6
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- Topic Modeling 9
- Natural Language Processing Techniques 3
- Text and Document Classification Technologies 3
- Sentiment Analysis and Opinion Mining 2
- Co-authors
- Houfeng Wang (6 shared papers)Sujian Li (5 shared papers)Xiaodong Zhang (3 shared papers)Lianzhe Huang (1 shared paper)Xing Xie (1 shared paper)Fangzhao Wu (1 shared paper)Xiyun Shan (11 shared papers)Lihua Li (6 shared papers)
In The Last Decade
Dehong Ma
24 papers receiving 670 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 414
- Public Health, Environmental and Occupational Health 163
- Infectious Diseases 81
- Information Systems 77
- Computer Vision and Pattern Recognition 48
Countries citing papers authored by Dehong Ma
This map shows the geographic impact of Dehong Ma'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 Dehong Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dehong Ma more than expected).
Fields of papers citing papers by Dehong Ma
This network shows the impact of papers produced by Dehong Ma. 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 Dehong Ma. The network helps show where Dehong Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Dehong Ma, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 206 | |
| 2 | 2019 | 99 | |
| 3 | 2014 | 65 | |
| 4 | 2018 | 46 | |
| 5 | 2020 | 41 | |
| 6 | 2021 | 41 | |
| 7 | 2018 | 31 | |
| 8 | 2021 | 22 | |
| 9 | 2018 | 18 | |
| 10 | 2018 | 17 | |
| 11 | 2016 | 14 | |
| 12 | Cascading Multiway Attentions for Document-level Sentiment Classification | 2017 | 14 |
| 13 | 2018 | 12 | |
| 14 | 2022 | 12 | |
| 15 | 2022 | 11 | |
| 16 | 2017 | 10 | |
| 17 | 2022 | 7 | |
| 18 | 2022 | 3 | |
| 19 | 2022 | 2 | |
| 20 | 2021 | 2 |
About Dehong Ma
Dehong Ma is a scholar working on Public Health, Environmental and Occupational Health, Artificial Intelligence, Infectious Diseases, Sociology and Political Science and Molecular Biology, having authored 26 papers that have together received 679 indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (13 papers), Topic Modeling (9 papers), Malaria Research and Control (6 papers), Viral Infections and Vectors (5 papers), Dengue and Mosquito Control Research (3 papers), Natural Language Processing Techniques (3 papers), Text and Document Classification Technologies (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Artificial Intelligence (414 citations), Public Health, Environmental and Occupational Health (163 citations), Infectious Diseases (81 citations), Information Systems (77 citations) and Computer Vision and Pattern Recognition (48 citations). Dehong Ma has collaborated with scholars based in China, Uganda and Belarus. Frequent co-authors include Houfeng Wang, Sujian Li, Xiaodong Zhang, Lianzhe Huang, Xing Xie, Fangzhao Wu, Xiyun Shan, Lihua Li, Linhao Zhang and Xiaohui Yan. Their work appears in journals such as Frontiers in Cellular and Infection Microbiology, International Journal of Infectious Diseases, Archives of Virology, Dyes and Pigments and Frontiers in Microbiology.
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.