Nan-Chen Chen

505 citations
14 papers · 325 · h-index 7

Impact in

Papers in

Nan-Chen Chen

14 papers receiving 315 citations

Peers

Nan-Chen Chen
Comparison fields: 5 of 83
  • Health Informatics 17
  • General Social Sciences 34
  • Computer Science Applications 37
  • Safety Research 50
  • Human-Computer Interaction 32
Replace Margaret Drouhard with:
Margaret Drouhard United States
Angelina Wang United States
Mitchell Gordon United States
Laria Reynolds United States
Kyle McDonell United States
Hariharan Subramonyam United States
Savvas Petridis United States
Marcin Gruza Poland
Bartłomiej Koptyra Poland
Linxuan Zhao Australia
Nan-Chen Chen relative to Margaret Drouhard United States Margaret Drouhard's profile →
Citations per field
00.5×1.7×
Margaret Drouhard · 1×
Citations per year

Countries citing papers authored by Nan-Chen Chen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

The 25 scholars most cited alongside Nan-Chen 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 Nan-Chen Chen Line = papers co-authored together Nan-Chen Chen links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201899
2 201897
3 201729
4 201826
5 201918
6 201117
7 201212
8 20176
9 20176
10 20175
11 20144
12 20172
13
A Cross-Cultural Survey of Emoticon Research Before 2015
20202
14 20142

About Nan-Chen Chen

Nan-Chen Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Sociology and Political Science and Language and Linguistics, having authored 14 papers that have together received 325 indexed citations. Recurring topics across this work include Data Visualization and Analytics (7 papers), Digital Communication and Language (3 papers), Language, Discourse, Communication Strategies (2 papers), Energy Efficiency and Management (2 papers), Hate Speech and Cyberbullying Detection (2 papers), Data Stream Mining Techniques (2 papers), Video Analysis and Summarization (2 papers) and Building Energy and Comfort Optimization (2 papers). The work is most often cited by research in Health Informatics (17 citations), General Social Sciences (34 citations), Computer Science Applications (37 citations), Safety Research (50 citations) and Human-Computer Interaction (32 citations). Nan-Chen Chen has collaborated with scholars based in United States, Taiwan and Chile. Frequent co-authors include Jina Suh, Gonzalo Ramos, C. Aragon, Rafał Kocielnik, Qian Yang, Margaret Drouhard, Steven M. Drucker, Patrice Simard, Hao-Hua Chu and Xiangyi Zheng. Their work appears in journals such as ACM Transactions on Interactive Intelligent Systems, Journal of the Association for Information Systems, Bilingualism Language and Cognition, Journal of the Association for Information Science and Technology and ResearchWorks at the University of Washington (University of Washington).

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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