Xiaodan Zhu
- Artificial Intelligence top 0.2%
- Computer Vision and Pattern Recognition top 1%
- Information Systems top 1%
- Sociology and Political Science top 5%
- Molecular Biology
- Co-authors
- Svetlana KiritchenkoSaif M. MohammadColin CherrySeyed MohammadParinaz SobhaniJoel MartinZhenming LiuZhen-Hua Ling
- Topics
- Topic Modeling (82 papers)Natural Language Processing Techniques (54 papers)Sentiment Analysis and Opinion Mining (22 papers)
- Partner nations
- CanadaChinaUnited States
In The Last Decade
Xiaodan Zhu
164 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Artificial Intelligence 3.9k
- Computer Vision and Pattern Recognition 690
- Information Systems 531
- Sociology and Political Science 523
- Molecular Biology 340
Countries citing papers authored by Xiaodan Zhu
This map shows the geographic impact of Xiaodan Zhu'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 Xiaodan Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaodan Zhu more than expected).
Fields of papers citing papers by Xiaodan Zhu
This network shows the impact of papers produced by Xiaodan Zhu. 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 Xiaodan Zhu. The network helps show where Xiaodan Zhu may publish in the future.
Co-authorship network of co-authors of Xiaodan Zhu
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaodan Zhu. A scholar is included among the top collaborators of Xiaodan Zhu 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 Xiaodan Zhu. Xiaodan Zhu 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 | 2 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | 1 | |
| 11 | 16 | |
| 12 | DeepDecision: A Mobile Deep Learning Framework for Edge Video Analyticsbreakdown → | 309 |
| 13 | 87 | |
| 14 | SemEval-2016 Task 6: Detecting Stance in Tweetsbreakdown → | 488 |
| 15 | 21 | |
| 16 | A Dataset for Detecting Stance in Tweets. | 47 |
| 17 | 2 | |
| 18 | Sentiment Analysis of Short Informal Textsbreakdown → | 588 |
| 19 | Sentiment Analysis of Social Media Texts | 0 |
| 20 | A Critical Reassessment of Evaluation Baselines for Speech Summarization | 48 |
About Xiaodan Zhu
Xiaodan Zhu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 181 papers that have together received 5.5k indexed citations. Recurring topics across this work include Topic Modeling (82 papers), Natural Language Processing Techniques (54 papers) and Sentiment Analysis and Opinion Mining (22 papers). The work is most often cited by research in Artificial Intelligence (3.9k citations), Computer Vision and Pattern Recognition (690 citations) and Human-Computer Interaction (150 citations). Xiaodan Zhu has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Svetlana Kiritchenko, Saif M. Mohammad, Colin Cherry, Seyed Mohammad, Parinaz Sobhani, Joel Martin, Zhenming Liu, Zhen-Hua Ling, Diana Inkpen and Hongyu Guo. Their work appears in journals such as Journal of Hazardous Materials, Physics Letters B and Journal of Chromatography A.
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.