Minsun Shim

1.6k total citations
34 papers, 1.2k citations indexed

About

Minsun Shim is a scholar working on Sociology and Political Science, General Health Professions and Literature and Literary Theory. According to data from OpenAlex, Minsun Shim has authored 34 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Sociology and Political Science, 9 papers in General Health Professions and 7 papers in Literature and Literary Theory. Recurrent topics in Minsun Shim's work include Health Literacy and Information Accessibility (9 papers), Media Influence and Health (7 papers) and Behavioral Health and Interventions (7 papers). Minsun Shim is often cited by papers focused on Health Literacy and Information Accessibility (9 papers), Media Influence and Health (7 papers) and Behavioral Health and Interventions (7 papers). Minsun Shim collaborates with scholars based in South Korea, United States and Malaysia. Minsun Shim's co-authors include Robert Hornik, Bridget Kelly, Jiran Hou, Heui Sug Jo, Roselyn J. Lee-Won, Jeong Yeob Han, Sung Gwan Park, Myoungsoon You, Joseph N. Cappella and Min Ju Lee and has published in prestigious journals such as Computers in Human Behavior, Journal of Communication and International Journal of Medical Informatics.

In The Last Decade

Minsun Shim

28 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Minsun Shim South Korea 14 608 414 196 195 156 34 1.2k
Shaohai Jiang Singapore 22 594 1.0× 635 1.5× 341 1.7× 168 0.9× 145 0.9× 55 1.4k
Piper Liping Liu Macao 17 492 0.8× 277 0.7× 201 1.0× 186 1.0× 71 0.5× 45 1.0k
Christopher E. Beaudoin United States 23 960 1.6× 325 0.8× 196 1.0× 538 2.8× 195 1.3× 56 1.8k
Nick Carcioppolo United States 18 436 0.7× 216 0.5× 101 0.5× 133 0.7× 227 1.5× 45 949
Jingyuan Shi Hong Kong 15 568 0.9× 223 0.5× 170 0.9× 223 1.1× 149 1.0× 42 1.0k
Jessica Fitts Willoughby United States 20 517 0.9× 403 1.0× 156 0.8× 196 1.0× 145 0.9× 77 1.2k
Itzhak Yanovitzky United States 19 570 0.9× 250 0.6× 103 0.5× 300 1.5× 250 1.6× 35 1.4k
Edmund W. J. Lee Singapore 19 699 1.1× 151 0.4× 88 0.4× 254 1.3× 138 0.9× 51 1.0k
Susannah Fox United States 13 427 0.7× 573 1.4× 222 1.1× 210 1.1× 119 0.8× 16 1.3k
Qinghua Yang United States 18 452 0.7× 212 0.5× 114 0.6× 128 0.7× 209 1.3× 50 904

Countries citing papers authored by Minsun Shim

Since Specialization
Citations

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

Fields of papers citing papers by Minsun Shim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minsun Shim

This figure shows the co-authorship network connecting the top 25 collaborators of Minsun Shim. A scholar is included among the top collaborators of Minsun Shim 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 Minsun Shim. Minsun Shim 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.
So, Jiyeon, Minsun Shim, & Hayeon Song. (2023). Diffusion of COVID-19 misinformation: Mechanisms for threat- and efficacy-related misinformation diffusion. Computers in Human Behavior. 149. 107967–107967. 1 indexed citations
2.
Chung, Sungeun, et al.. (2022). Types of Perceived Risk Likelihood and Prediction of Preventive Behaviors : Absolute vs. Comparative, and Conditional vs. Unconditional Risk Perceptions. Korean Journal of Journalism & Communication Studies. 66(2). 155–187. 1 indexed citations
3.
Song, Hayeon, et al.. (2022). What message features influence the intention to share misinformation about COVID-19 on social media? The role of efficacy and novelty. Computers in Human Behavior. 138. 107439–107439. 30 indexed citations
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7.
Shim, Minsun & Heui Sug Jo. (2020). What quality factors matter in enhancing the perceived benefits of online health information sites? Application of the updated DeLone and McLean Information Systems Success Model. International Journal of Medical Informatics. 137. 104093–104093. 139 indexed citations
8.
You, Myoungsoon, Jeongsub Lim, Minsun Shim, & Youngkee Ju. (2018). Outrage effects on food risk perception as moderated by risk attitude. Journal of Risk Research. 22(12). 1522–1531. 16 indexed citations
9.
Choung, Ji Tae, et al.. (2017). What Factors Impact Consumer Perception of the Effectiveness of Health Information Sites? An Investigation of the Korean National Health Information Portal. Journal of Korean Medical Science. 32(7). 1077–1077. 5 indexed citations
10.
Shim, Minsun, et al.. (2016). News Portrayal of Cancer: Content Analysis of Threat and Efficacy by Cancer Type and Comparison with Incidence and Mortality in Korea. Journal of Korean Medical Science. 31(8). 1231–1231. 8 indexed citations
11.
Kim, Yong‐Chan, Minsun Shim, Jee Hyun Kim, et al.. (2015). Cancer Risk Factors in Korean News Media: a Content Analysis. Asian Pacific Journal of Cancer Prevention. 16(2). 731–736. 8 indexed citations
12.
Ju, Youngkee, Jeongsub Lim, Minsun Shim, & Myoungsoon You. (2015). Outrage Factors in Government Press Releases of Food Risk and Their Influence on News Media Coverage. Journal of Health Communication. 20(8). 879–887. 18 indexed citations
13.
Shim, Minsun, Laura M. Mercer Kollar, Linda J. Roberts, & David H. Gustafson. (2015). Communication Competence, Psychological Well-Being, and the Mediating Role of Coping Efforts Among Women With Breast Cancer: Cross-Sectional and Longitudinal Evidence. Women & Health. 55(4). 400–418. 7 indexed citations
14.
Shim, Minsun & Myoungsoon You. (2015). Cognitive and affective risk perceptions toward food safety outbreaks: mediating the relation between news use and food consumption intention. Asian Journal of Communication. 25(1). 48–64. 43 indexed citations
15.
Han, Jeong Yeob, Jung-Hyun Kim, Hye Jin Yoon, et al.. (2011). Social and Psychological Determinants of Levels of Engagement With an Online Breast Cancer Support Group: Posters, Lurkers, and Nonusers. Journal of Health Communication. 17(3). 356–371. 64 indexed citations
16.
Shim, Minsun, Joseph N. Cappella, & Jeong Yeob Han. (2011). How Does Insightful and Emotional Disclosure Bring Potential Health Benefits? Study Based on Online Support Groups for Women With Breast Cancer. Journal of Communication. 61(3). 432–454. 80 indexed citations
17.
Shim, Minsun, et al.. (2008). Photograph Use on Social Network Sites among South Korean College Students: The Role of Public and Private Self-Consciousness. CyberPsychology & Behavior. 11(4). 489–493. 44 indexed citations
18.
Shim, Minsun. (2008). Self-disclosure in online support groups: The patterns of disclosure and their potential health benefits for women with breast cancer. Scholarly Commons (University of Pennsylvania). 1 indexed citations
19.
Shim, Minsun. (2008). Connecting Internet Use with Gaps in Cancer Knowledge. Health Communication. 23(5). 448–461. 52 indexed citations
20.
Shim, Minsun, Bridget Kelly, & Robert Hornik. (2006). Cancer Information Scanning and Seeking Behavior is Associated with Knowledge, Lifestyle Choices, and Screening. Journal of Health Communication. 11(sup001). 157–172. 320 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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