Sungjun Won

808 citations
16 papers · 493 · h-index 10

Impact in

Papers in

Sungjun Won

15 papers receiving 473 citations

Peers

Sungjun Won
Comparison fields: 5 of 50
  • Clinical Psychology 200
  • Developmental and Educational Psychology 112
  • Experimental and Cognitive Psychology 116
  • Social Psychology 171
  • Computer Science Applications 43
Replace Raven Rinas with:
Raven Rinas Germany
Valeria Negovan Romania
Amparo Gómez-Artiga Spain
Fernando Doménech-Betoret Spain
Hyeonsook Shin South Korea
Wenye Zhou China
Norma S. Guerra United States
Tuomo Virtanen Finland
Jennifer Cunha Portugal
María Carmen González Torres Spain
Sungjun Won relative to Raven Rinas Germany Raven Rinas's profile →
Citations per field
00.5×9.6×
Raven Rinas · 1×
Citations per year

Countries citing papers authored by Sungjun Won

Since Specialization
Citations

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

Fields of papers citing papers by Sungjun Won

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Sungjun Won, 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 Sungjun Won Line = papers co-authored together Sungjun Won links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2017118
2 201784
3 201973
4 201768
5 201837
6 201730
7 201730
8 201920
9 202310
10 202210
11 20185
12 20204
13 20242
14 20241
15 20211
16 20250

About Sungjun Won

Sungjun Won is a scholar working on Social Psychology, Clinical Psychology, Education, Sociology and Political Science and Safety Research, having authored 16 papers that have together received 493 indexed citations. Recurring topics across this work include Perfectionism, Procrastination, Anxiety Studies (4 papers), Motivation and Self-Concept in Sports (4 papers), Education, Achievement, and Giftedness (3 papers), Grit, Self-Efficacy, and Motivation (3 papers), Child Welfare and Adoption (2 papers), Early Childhood Education and Development (2 papers), Innovative Teaching and Learning Methods (2 papers) and Parental Involvement in Education (2 papers). The work is most often cited by research in Clinical Psychology (200 citations), Developmental and Educational Psychology (112 citations), Experimental and Cognitive Psychology (116 citations), Social Psychology (171 citations) and Computer Science Applications (43 citations). Sungjun Won has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Christopher A. Wolters, Shirley L. Yu, Lauren Hensley, Eric M. Anderman, Sun-Young Lee, Mimi Bong, Anna C. Brady, Rick S. Zimmerman, Alison C. Koenka and Lynley H. Anderman. Their work appears in journals such as The Journal of Experimental Education, Learning and Individual Differences, Contemporary Educational Psychology, Frontiers in Psychology and Social Psychology of Education.

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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