Youngmi Song
About
In The Last Decade
Youngmi Song
10 papers receiving 255 citations
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 87
- Accounting 45
- Cardiology and Cardiovascular Medicine 41
- Molecular Biology 38
- Endocrinology, Diabetes and Metabolism 38
Countries citing papers authored by Youngmi Song
This map shows the geographic impact of Youngmi Song'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 Youngmi Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youngmi Song more than expected).
Fields of papers citing papers by Youngmi Song
This network shows the impact of papers produced by Youngmi Song. 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 Youngmi Song. The network helps show where Youngmi Song may publish in the future.
Co-authorship network of co-authors of Youngmi Song
This figure shows the co-authorship network connecting the top 25 collaborators of Youngmi Song. A scholar is included among the top collaborators of Youngmi Song 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 Youngmi Song. Youngmi Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 12 | |
| 4 | 50 | |
| 5 | 17 | |
| 6 | 97 | |
| 7 | 2 | |
| 8 | 30 | |
| 9 | 8 | |
| 10 | 47 |
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.