Nan‐Chen Chen
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Safety Research top 10%
- Information Systems
- General Social Sciences top 2%
- Co-authors
- Jina SuhGonzalo RamosC. AragonQian YangRafał KocielnikMargaret DrouhardPatrice SimardSteven M. Drucker
- Topics
- Data Visualization and Analytics (7 papers)Digital Communication and Language (3 papers)Hate Speech and Cyberbullying Detection (2 papers)
- Journals
- Bilingualism Language and CognitionJournal of the Association for Information Science and TechnologyACM Transactions on Interactive Intelligent Systems
- Partner nations
- United StatesChile
In The Last Decade
Nan‐Chen Chen
11 papers receiving 270 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 139
- Computer Vision and Pattern Recognition 71
- Safety Research 50
- Information Systems 41
- General Social Sciences 34
Countries citing papers authored by Nan‐Chen Chen
This map shows the geographic impact of Nan‐Chen 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 Nan‐Chen Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan‐Chen Chen more than expected).
Fields of papers citing papers by Nan‐Chen Chen
This network shows the impact of papers produced by Nan‐Chen 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 Nan‐Chen Chen. The network helps show where Nan‐Chen Chen may publish in the future.
Co-authorship network of co-authors of Nan‐Chen Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Nan‐Chen Chen. A scholar is included among the top collaborators of Nan‐Chen Chen 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 Nan‐Chen Chen. Nan‐Chen Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Cross-Cultural Survey of Emoticon Research Before 2015 | 2 |
| 2 | 16 | |
| 3 | 26 | |
| 4 | 94 | |
| 5 | 92 | |
| 6 | 2 | |
| 7 | 27 | |
| 8 | 6 | |
| 9 | 6 | |
| 10 | 5 | |
| 11 | 4 |
About Nan‐Chen Chen
Nan‐Chen Chen is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and General Social Sciences, having authored 11 papers that have together received 280 indexed citations. Recurring topics across this work include Data Visualization and Analytics (7 papers), Digital Communication and Language (3 papers) and Hate Speech and Cyberbullying Detection (2 papers). The work is most often cited by research in Health Informatics (16 citations), General Social Sciences (34 citations) and Computer Science Applications (34 citations). Nan‐Chen Chen has collaborated with scholars based in United States and Chile. Frequent co-authors include Jina Suh, Gonzalo Ramos, C. Aragon, Qian Yang, Rafał Kocielnik, Margaret Drouhard, Patrice Simard, Steven M. Drucker, Xiangyi Zheng and Judith F. Kroll. Their work appears in journals such as Bilingualism Language and Cognition, Journal of the Association for Information Science and Technology and ACM Transactions on Interactive Intelligent Systems.
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.