Sunmoo Yoon

1.5k total citations
47 papers, 954 citations indexed

About

Sunmoo Yoon is a scholar working on General Health Professions, Social Psychology and Sociology and Political Science. According to data from OpenAlex, Sunmoo Yoon has authored 47 papers receiving a total of 954 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in General Health Professions, 10 papers in Social Psychology and 9 papers in Sociology and Political Science. Recurrent topics in Sunmoo Yoon's work include Mental Health via Writing (9 papers), Health Literacy and Information Accessibility (8 papers) and Physical Activity and Health (5 papers). Sunmoo Yoon is often cited by papers focused on Mental Health via Writing (9 papers), Health Literacy and Information Accessibility (8 papers) and Physical Activity and Health (5 papers). Sunmoo Yoon collaborates with scholars based in United States, South Korea and Norway. Sunmoo Yoon's co-authors include Michelle Odlum, Suzanne Bakken, Ian M. Kronish, Karina W. Davidson, Nathalie Moise, Niurka Suero-Tejeda, Noémie Elhadad, Jacqueline Merrill, Louise Falzon and Jeffrey L. Birk and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Preventive Medicine and Health Psychology.

In The Last Decade

Sunmoo Yoon

44 papers receiving 917 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sunmoo Yoon United States 14 316 251 186 158 107 47 954
Kevin Padrez United States 12 213 0.7× 250 1.0× 132 0.7× 230 1.5× 111 1.0× 15 982
Sunny Jung Kim United States 16 222 0.7× 288 1.1× 92 0.5× 140 0.9× 103 1.0× 36 924
Lauren Sinnenberg United States 10 161 0.5× 235 0.9× 114 0.6× 234 1.5× 108 1.0× 13 801
Tsuyoshi Okuhara Japan 17 253 0.8× 188 0.7× 110 0.6× 220 1.4× 122 1.1× 101 873
Wura Jacobs United States 13 332 1.1× 216 0.9× 155 0.8× 207 1.3× 101 0.9× 42 877
Carolyn Lauckner United States 13 376 1.2× 276 1.1× 119 0.6× 105 0.7× 90 0.8× 35 860
Christina Mancheno United States 6 146 0.5× 231 0.9× 98 0.5× 241 1.5× 64 0.6× 10 608
Theodore L. Caputi United States 17 143 0.5× 152 0.6× 148 0.8× 131 0.8× 127 1.2× 32 885
Osman Hassan Ahmed United Kingdom 17 316 1.0× 184 0.7× 303 1.6× 215 1.4× 220 2.1× 60 1.0k
Jon Agley United States 18 286 0.9× 321 1.3× 392 2.1× 220 1.4× 362 3.4× 102 1.3k

Countries citing papers authored by Sunmoo Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Sunmoo Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunmoo Yoon

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

All Works

20 of 20 papers shown
1.
Liu, Jianfang, et al.. (2023). Analyzing Twitter-Based Social Networks of Support Communities for Hispanic and African American Family Caregivers of Persons with Dementia. Studies in health technology and informatics. 305. 155–159.
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Wang, Y Claire, Elizabeth Brondolo, Michaela Kiernan, et al.. (2021). Introducing the MAVEN Leadership Training Initiative to diversify the scientific workforce. eLife. 10. 5 indexed citations
6.
Birk, Jeffrey L., Ian M. Kronish, Nathalie Moise, et al.. (2019). Depression and multimorbidity: Considering temporal characteristics of the associations between depression and multiple chronic diseases.. Health Psychology. 38(9). 802–811. 121 indexed citations
7.
Yoon, Sunmoo, Louise Falzon, Norman B. Anderson, & Karina W. Davidson. (2019). A look at the increasing demographic representation within behavioral medicine. Journal of Behavioral Medicine. 42(1). 57–66. 2 indexed citations
8.
Lor, Maichou, et al.. (2019). Association Between Health Literacy and Medication Adherence Among Hispanics with Hypertension. Journal of Racial and Ethnic Health Disparities. 6(3). 517–524. 55 indexed citations
9.
Diaz, Keith M., Anusorn Thanataveerat, Faith Parsons, et al.. (2018). The Influence of Daily Stress on Sedentary Behavior: Group and Person (N of 1) Level Results of a 1-Year Observational Study. Psychosomatic Medicine. 80(7). 620–627. 16 indexed citations
10.
Odlum, Michelle & Sunmoo Yoon. (2018). Health Information Needs and Health Seeking Behavior During the 2014-2016 Ebola Outbreak: A Twitter Content Analysis. PLoS Currents. 10. 24 indexed citations
11.
Yoon, Sunmoo, Joseph E. Schwartz, Matthew M. Burg, et al.. (2018). Using Behavioral Analytics to Increase Exercise: A Randomized N-of-1 Study. American Journal of Preventive Medicine. 54(4). 559–567. 15 indexed citations
12.
Yoon, Sunmoo, Thomas Y. Choi, Michelle Odlum, et al.. (2018). Machine Learning to Identify Behavioral Determinants of Oral Health in Inner City Older Hispanic Adults. Studies in health technology and informatics. 251. 253–256. 6 indexed citations
13.
Tsimicalis, Argerie, Sylvie Le May, Jennifer Stinson, et al.. (2016). Linguistic Validation of an Interactive Communication Tool to Help French-Speaking Children Express Their Cancer Symptoms. Journal of Pediatric Oncology Nursing. 34(2). 98–105. 11 indexed citations
14.
Yoon, Sunmoo, Jonathan A. Shaffer, & Suzanne Bakken. (2015). Refining a self-assessment of informatics competency scale using Mokken scaling analysis. Journal of Interprofessional Care. 29(6). 579–586. 22 indexed citations
15.
Odlum, Michelle & Sunmoo Yoon. (2015). What can we learn about the Ebola outbreak from tweets?. American Journal of Infection Control. 43(6). 563–571. 179 indexed citations
16.
Yoon, Sunmoo & José Gutierrez. (2015). Behavior Correlates of Post-Stroke Disability Using Data Mining and Infographics. British Journal of Medicine and Medical Research. 11(5). 1–12. 2 indexed citations
17.
Collins, Sarah, et al.. (2014). Digital divide and information needs for improving family support among the poor and underserved. Health Informatics Journal. 22(1). 67–77. 10 indexed citations
18.
Yoon, Sunmoo, Noémie Elhadad, & Suzanne Bakken. (2013). A Practical Approach for Content Mining of Tweets. American Journal of Preventive Medicine. 45(1). 122–129. 65 indexed citations
19.
Yoon, Sunmoo, Adam Wilcox, & Suzanne Bakken. (2013). Comparisons Among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures that Support Comparative Effectiveness Research. SHILAP Revista de lepidopterología. 1(1). 9–9. 10 indexed citations
20.
Merrill, Jacqueline, Sunmoo Yoon, Elaine Larson, Judy Honig, & Nancy King Reame. (2012). Using social network analysis to examine collaborative relationships among PhD and DNP students and faculty in a research-intensive university school of nursing. Nursing Outlook. 61(2). 109–116. 12 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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