Eunice Jun
Impact in
- Human-Computer Interaction top 5%
- Virtual Reality Applications and Impacts
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
Papers in
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- Data Visualization and Analytics 7
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- Data Analysis with R 2
- Co-authors
- Katharina Reinecke (5 shared papers)Jeffrey Heer (4 shared papers)Qisheng Li (1 shared paper)Gary Hsieh (1 shared paper)Daniel McDuff (2 shared papers)Mary Czerwinski (2 shared papers)Michael N. Geuss (1 shared paper)Jeanine K. Stefanucci (1 shared paper)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (3 papers)Computer Graphics Forum (1 paper)Health Affairs (1 paper)ACM Transactions on Computer-Human Interaction (1 paper)IEEE Transactions on Affective Computing (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Eunice Jun
16 papers receiving 237 citations
Peers
Comparison fields: 5 of 78
- Human-Computer Interaction 56
- Computer Science Applications 23
- Information Systems and Management 22
- Applied Psychology 16
- Cognitive Neuroscience 54
Countries citing papers authored by Eunice Jun
This map shows the geographic impact of Eunice Jun'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 Eunice Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eunice Jun more than expected).
Fields of papers citing papers by Eunice Jun
This network shows the impact of papers produced by Eunice Jun. 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 Eunice Jun. The network helps show where Eunice Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside Eunice Jun, 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 | 2019 | 55 | |
| 2 | 2015 | 40 | |
| 3 | 2017 | 38 | |
| 4 | 2019 | 20 | |
| 5 | 2017 | 14 | |
| 6 | 2018 | 12 | |
| 7 | 2022 | 11 | |
| 8 | 2019 | 11 | |
| 9 | 2022 | 10 | |
| 10 | 2022 | 9 | |
| 11 | 2023 | 8 | |
| 12 | 2022 | 5 | |
| 13 | 2025 | 3 | |
| 14 | 2018 | 3 | |
| 15 | 2022 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2017 | 1 | |
| 18 | 2024 | 0 | |
| 19 | 2024 | 0 | |
| 20 | 2025 | 0 |
About Eunice Jun
Eunice Jun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Science Applications, Information Systems and Management and Sociology and Political Science, having authored 20 papers that have together received 242 indexed citations. Recurring topics across this work include Data Visualization and Analytics (7 papers), Mobile Crowdsensing and Crowdsourcing (5 papers), Scientific Computing and Data Management (4 papers), Open Source Software Innovations (3 papers), Software Engineering Research (2 papers), Data Analysis with R (2 papers), 3D Shape Modeling and Analysis (2 papers) and Misinformation and Its Impacts (2 papers). The work is most often cited by research in Human-Computer Interaction (56 citations), Computer Science Applications (23 citations), Information Systems and Management (22 citations), Applied Psychology (16 citations) and Cognitive Neuroscience (54 citations). Eunice Jun has collaborated with scholars based in United States and Germany. Frequent co-authors include Katharina Reinecke, Jeffrey Heer, Qisheng Li, Gary Hsieh, Daniel McDuff, Mary Czerwinski, Michael N. Geuss, Jeanine K. Stefanucci, Sarah H. Creem-Regehr and William B. Thompson. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Computer Graphics Forum, Health Affairs, ACM Transactions on Computer-Human Interaction and IEEE Transactions on Affective Computing.
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.