Hang-Hyun Jo
- Statistical and Nonlinear Physics top 1%
- Sociology and Political Science top 10%
- Transportation top 2%
- Economics and Econometrics top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Kimmo KaskiJános KertészRaj Kumar PanJános TörökYohsuke MuraseMárton KarsaiHie‐Tae MoonEun‐Kyeong Kim
- Topics
- Complex Network Analysis Techniques (45 papers)Opinion Dynamics and Social Influence (39 papers)Complex Systems and Time Series Analysis (17 papers)
- Partner nations
- South KoreaFinlandUnited Kingdom
In The Last Decade
Hang-Hyun Jo
62 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 167
- Statistical and Nonlinear Physics 550
- Sociology and Political Science 201
- Transportation 165
- Economics and Econometrics 116
- Computer Networks and Communications 113
Countries citing papers authored by Hang-Hyun Jo
This map shows the geographic impact of Hang-Hyun Jo'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 Hang-Hyun Jo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang-Hyun Jo more than expected).
Fields of papers citing papers by Hang-Hyun Jo
This network shows the impact of papers produced by Hang-Hyun Jo. 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 Hang-Hyun Jo. The network helps show where Hang-Hyun Jo may publish in the future.
Co-authorship network of co-authors of Hang-Hyun Jo
This figure shows the co-authorship network connecting the top 25 collaborators of Hang-Hyun Jo. A scholar is included among the top collaborators of Hang-Hyun Jo 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 Hang-Hyun Jo. Hang-Hyun Jo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 17 | |
| 6 | 84 | |
| 7 | 9 | |
| 8 | 8 | |
| 9 | 9 | |
| 10 | 26 | |
| 11 | Dynamics of close relationships for the life-course migration. | 2 |
| 12 | Generalized friendship paradox in complex networks | 5 |
| 13 | 25 | |
| 14 | 47 | |
| 15 | 25 | |
| 16 | 3 | |
| 17 | Circadian pattern and burstiness in human communication activity | 8 |
| 18 | The Coevolution of Cooperation and Trait Distinction | 1 |
| 19 | Detrended fluctuation analysis in the Korean bond futures exchange market | 1 |
| 20 | 47 |
About Hang-Hyun Jo
Hang-Hyun Jo is a scholar working on Statistical and Nonlinear Physics, Transportation and Economics and Econometrics, having authored 67 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (45 papers), Opinion Dynamics and Social Influence (39 papers) and Complex Systems and Time Series Analysis (17 papers). The work is most often cited by research in Statistical and Nonlinear Physics (550 citations), Transportation (165 citations) and Communication (55 citations). Hang-Hyun Jo has collaborated with scholars based in South Korea, Finland and United Kingdom. Frequent co-authors include Kimmo Kaski, János Kertész, Raj Kumar Pan, János Török, Yohsuke Murase, Márton Karsai, Hie‐Tae Moon, Eun‐Kyeong Kim, Jari Saramäki and Okyu Kwon. Their work appears in journals such as Physical Review Letters, PLoS ONE and Scientific Reports.
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.