Rui Mao
- Artificial Intelligence top 1%
- Experimental and Cognitive Psychology top 5%
- Management Science and Operations Research top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Co-authors
- Erik CambriaKai HeChenghua LinFrank GuérinWei LiQika LinQian LiuXiao Li
- Topics
- Topic Modeling (30 papers)Natural Language Processing Techniques (24 papers)Sentiment Analysis and Opinion Mining (18 papers)
- Partner nations
- SingaporeChinaUnited Kingdom
In The Last Decade
Rui Mao
92 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 1.0k
- Experimental and Cognitive Psychology 279
- Management Science and Operations Research 267
- Computer Vision and Pattern Recognition 160
- Information Systems 108
Countries citing papers authored by Rui Mao
This map shows the geographic impact of Rui Mao'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 Rui Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rui Mao more than expected).
Fields of papers citing papers by Rui Mao
This network shows the impact of papers produced by Rui Mao. 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 Rui Mao. The network helps show where Rui Mao may publish in the future.
Co-authorship network of co-authors of Rui Mao
This figure shows the co-authorship network connecting the top 25 collaborators of Rui Mao. A scholar is included among the top collaborators of Rui Mao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rui Mao. Rui Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 12 | |
| 6 | 24 | |
| 7 | 27 | |
| 8 | 11 | |
| 9 | 4 | |
| 10 | 49 | |
| 11 | 17 | |
| 12 | 18 | |
| 13 | 24 | |
| 14 | 67 | |
| 15 | 46 | |
| 16 | The Biases of Pre-Trained Language Models: An Empirical Study on Prompt-Based Sentiment Analysis and Emotion Detectionbreakdown → | 148 |
| 17 | 7 | |
| 18 | 3 | |
| 19 | 4 | |
| 20 | An Analysis of Some Problems on the Studies of "Left Behind Children" | 2 |
About Rui Mao
Rui Mao is a scholar working on Artificial Intelligence, Health Informatics and Experimental and Cognitive Psychology, having authored 103 papers that have together received 1.6k indexed citations. Recurring topics across this work include Topic Modeling (30 papers), Natural Language Processing Techniques (24 papers) and Sentiment Analysis and Opinion Mining (18 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Health Informatics (37 citations) and Management Science and Operations Research (267 citations). Rui Mao has collaborated with scholars based in Singapore, China and United Kingdom. Frequent co-authors include Erik Cambria, Kai He, Chenghua Lin, Frank Guérin, Wei Li, Qika Lin, Qian Liu, Xiao Li, Chen Li and Tieliang Gong. Their work appears in journals such as Journal of Medicinal Chemistry, Cerebral Cortex and Expert Systems with Applications.
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.