Guandan Chen

622 citations
9 papers · 483 · h-index 8

Impact in

Papers in

Journals
IEEE Transactions on Systems Man and Cybernetics Systems (1 paper)Neurocomputing (1 paper)IEEE International Conference on Intelligence and Security Informatics (ISI) (3 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)ACM International Conference on Information and Knowledge Management (CIKM) (1 paper)
Partner nations
China

In The Last Decade

Guandan Chen

9 papers receiving 472 citations

Peers

Guandan Chen
Comparison fields: 5 of 27
  • Artificial Intelligence 330
  • Statistical and Nonlinear Physics 45
  • Computer Vision and Pattern Recognition 55
  • Communication 19
  • Information Systems 43
Replace Sanasam Ranbir Singh with:
Sanasam Ranbir Singh India
Sandro Cavallari Singapore
Peng Lu Canada
Yutaka Kidawara Japan
Franco Salvetti United States
Kaisong Song China
Guillaume Erétéo France
Madhu Kumari India
Cane Wing-ki Leung Hong Kong
Guandan Chen relative to Sanasam Ranbir Singh India Sanasam Ranbir Singh's profile →
Citations per field
00.5×1.5×2.2×
Sanasam Ranbir Singh · 1×
Citations per year

Countries citing papers authored by Guandan Chen

Since Specialization
Citations

This map shows the geographic impact of Guandan Chen'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 Guandan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guandan Chen more than expected).

Fields of papers citing papers by Guandan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guandan Chen. 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 Guandan Chen. The network helps show where Guandan Chen may publish in the future.

Co-authors

The 3 scholars most cited alongside Guandan Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Guandan Chen Line = papers co-authored together Guandan Chen links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2019198
2 2018136
3 201852
4 201833
5 201819
6 201718
7 201711
8 201811
9 20185

About Guandan Chen

Guandan Chen is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Information Systems, Sociology and Political Science and Nuclear Energy and Engineering, having authored 9 papers that have together received 483 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Complex Network Analysis Techniques (3 papers), Misinformation and Its Impacts (3 papers), Recommender Systems and Techniques (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Text and Document Classification Technologies (1 paper) and Digital Marketing and Social Media (1 paper). The work is most often cited by research in Artificial Intelligence (330 citations), Statistical and Nonlinear Physics (45 citations), Computer Vision and Pattern Recognition (55 citations), Communication (19 citations) and Information Systems (43 citations). Guandan Chen has collaborated with scholars based in China. Frequent co-authors include Wenji Mao, Nan Xu and Daniel Dajun Zeng. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, Neurocomputing, IEEE International Conference on Intelligence and Security Informatics (ISI), Proceedings of the AAAI Conference on Artificial Intelligence and ACM International Conference on Information and Knowledge Management (CIKM).

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.

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