Xiuzhen Zhang
- Software top 5%
- Information Systems top 1%
- Spam and Phishing Detection 14
- Recommender Systems and Techniques 14
- Data Mining Algorithms and Applications 7
- Artificial Intelligence top 2%
- Topic Modeling 16
- Sentiment Analysis and Opinion Mining 12
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- Complex Network Analysis Techniques 13
- Communication top 10%
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- Misinformation and Its Impacts 10
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- Data Management and Algorithms 8
Xiuzhen Zhang
94 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 132
- Software 121
- Information Systems 670
- Artificial Intelligence 699
- Statistical and Nonlinear Physics 128
- Communication 56
Countries citing papers authored by Xiuzhen Zhang
This map shows the geographic impact of Xiuzhen Zhang'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 Xiuzhen Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiuzhen Zhang more than expected).
Fields of papers citing papers by Xiuzhen Zhang
This network shows the impact of papers produced by Xiuzhen Zhang. 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 Xiuzhen Zhang. The network helps show where Xiuzhen Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiuzhen Zhang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 3 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 0 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 4 | |
| 8 | 2021 | 9 | |
| 9 | RMIT at PAN-CLEF 2020: Profiling Fake News Spreaders on Twitter. | 2020 | 3 |
| 10 | Detection of money laundering groups: Supervised learning on small networks | 2017 | 16 |
| 11 | 2017 | 1 | |
| 12 | Anytime concurrent clustering of multiple streams with an indexing tree | 2015 | 2 |
| 13 | 2014 | 6 | |
| 14 | A List of New Record Families and Genera from Gansu & New Record Genera from China of Tenthredinidae(Hymenoptera:Symphyta) | 2012 | 1 |
| 15 | An empirical study of learning from imbalanced data | 2011 | 2 |
| 16 | Survey of semicarbazide contamination in coastal waters adjacent to the Chaohe River estuary. | 2010 | 9 |
| 17 | RMIT at TREC 2010 Blog Track: Faceted Blog Distillation Task | 2010 | 3 |
| 18 | The Melbourne Team at the TREC 2010 Legal Track. | 2010 | 2 |
| 19 | 2009 | 40 | |
| 20 | Drill across & visualization of cubes with non-conformed dimensions | 2008 | 6 |
About Xiuzhen Zhang
Xiuzhen Zhang is a scholar working on Information Systems, Artificial Intelligence and Signal Processing, having authored 104 papers that have together received 1.4k indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Spam and Phishing Detection (14 papers), Recommender Systems and Techniques (14 papers), Complex Network Analysis Techniques (13 papers), Sentiment Analysis and Opinion Mining (12 papers), Misinformation and Its Impacts (10 papers), Data Management and Algorithms (8 papers) and Data Mining Algorithms and Applications (7 papers). The work is most often cited by research in Software (121 citations), Information Systems (670 citations) and Artificial Intelligence (699 citations). Xiuzhen Zhang has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Hongyu Zhang, Yan Wang, Jeffrey Chan, Shiwei Zhang, Hua Wang, Shoujin Wang, Paolo Rosso, Kotagiri Ramamohanarao, Mark Sanderson and Min Peng. Their work appears in journals such as PLoS ONE, Computers in Human Behavior 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.