Sukwon Lee

663 total citations
11 papers, 434 citations indexed

About

Sukwon Lee is a scholar working on General Health Professions, Computer Vision and Pattern Recognition and Health Information Management. According to data from OpenAlex, Sukwon Lee has authored 11 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in General Health Professions, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Health Information Management. Recurrent topics in Sukwon Lee's work include Data Visualization and Analytics (4 papers), Health Literacy and Information Accessibility (3 papers) and Global Cancer Incidence and Screening (2 papers). Sukwon Lee is often cited by papers focused on Data Visualization and Analytics (4 papers), Health Literacy and Information Accessibility (3 papers) and Global Cancer Incidence and Screening (2 papers). Sukwon Lee collaborates with scholars based in United States, South Korea and Germany. Sukwon Lee's co-authors include Sung-Hee Kim, Bum Chul Kwon, Ji Soo Yi, Heidi Lam, Younah Kang, Jina Huh, Jaegul Choo, Minje Choi, Jihoon Kim and Byung Cheol Lee and has published in prestigious journals such as Journal of Medical Internet Research, Preventive Medicine and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Sukwon Lee

11 papers receiving 416 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sukwon Lee United States 6 226 94 90 56 47 11 434
Ha‐Kyung Kong United States 10 160 0.7× 95 1.0× 78 0.9× 37 0.7× 20 0.4× 20 343
Rahul Bhargava United States 9 43 0.2× 49 0.5× 83 0.9× 34 0.6× 8 0.2× 19 279
Zhenhui Peng Hong Kong 12 31 0.1× 169 1.8× 65 0.7× 42 0.8× 19 0.4× 38 375
Alexandru Balog Romania 10 146 0.6× 31 0.3× 86 1.0× 106 1.9× 16 0.3× 36 435
Melanie Feinberg United States 12 52 0.2× 72 0.8× 104 1.2× 97 1.7× 37 0.8× 36 446
Patrick Ehlen United States 12 33 0.1× 333 3.5× 112 1.2× 68 1.2× 20 0.4× 34 524
Zhiyuan Lin United States 9 63 0.3× 142 1.5× 143 1.6× 27 0.5× 17 0.4× 20 424
Alice Thudt Canada 7 150 0.7× 34 0.4× 61 0.7× 94 1.7× 15 0.3× 12 305
Debora Weber-Wulff Germany 9 39 0.2× 146 1.6× 64 0.7× 56 1.0× 10 0.2× 18 578
Mireia Ribera Spain 11 44 0.2× 128 1.4× 60 0.7× 80 1.4× 21 0.4× 59 675

Countries citing papers authored by Sukwon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sukwon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sukwon Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Sukwon Lee. A scholar is included among the top collaborators of Sukwon Lee 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 Sukwon Lee. Sukwon Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
2.
3.
Lee, Sukwon, et al.. (2019). The Correlation between Users’ Cognitive Characteristics and Visualization Literacy. Applied Sciences. 9(3). 488–488. 27 indexed citations
4.
Lee, Sukwon, et al.. (2017). Toward Predicting Social Support Needs in Online Health Social Networks. Journal of Medical Internet Research. 19(8). e272–e272. 15 indexed citations
5.
Huh, Jina, Bum Chul Kwon, Sung-Hee Kim, et al.. (2016). Personas in online health communities. Journal of Biomedical Informatics. 63. 212–225. 68 indexed citations
6.
Lee, Sukwon, Sung-Hee Kim, & Bum Chul Kwon. (2016). <italic>VLAT</italic>: Development of a Visualization Literacy Assessment Test. IEEE Transactions on Visualization and Computer Graphics. 23(1). 551–560. 168 indexed citations
7.
Kwon, Bum Chul, Sung-Hee Kim, Sukwon Lee, et al.. (2015). VisOHC: Designing Visual Analytics for Online Health Communities. IEEE Transactions on Visualization and Computer Graphics. 22(1). 71–80. 33 indexed citations
8.
Wang, Yanyan, Iris Xie, & Sukwon Lee. (2015). Explore eye movement patterns in search result evaluation and individual document evaluation. Proceedings of the Association for Information Science and Technology. 52(1). 1–4. 3 indexed citations
9.
Lee, Sukwon, et al.. (2015). How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice's Information Visualization Sensemaking. IEEE Transactions on Visualization and Computer Graphics. 22(1). 499–508. 110 indexed citations
10.
Lee, Sukwon, et al.. (2015). What Are the Causes of Noncompliance Behaviors in Bar Code Medication Administration System Processes?. International Journal of Human-Computer Interaction. 31(4). 227–252. 2 indexed citations
11.
Park, Jong Hyuk, et al.. (2006). DRBAC Model Using a WSNM for Services in i-Home. IEICE Transactions on Information and Systems. E89-D(12). 2831–2837. 2 indexed citations

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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