Yu‐Ru Lin
Impact in
- Computational Mathematics top 1%
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
-
- Complex Network Analysis Techniques 51
- Opinion Dynamics and Social Influence 29
-
- Topic Modeling 9
- Co-authors
- Hari Sundaram (22 shared papers)Yün Chi (8 shared papers)Belle L. Tseng (8 shared papers)Nan Cao (18 shared papers)Shenghuo Zhu (2 shared papers)Lada A. Adamic (1 shared paper)Drew Margolin (12 shared papers)Xidao Wen (13 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (7 papers)EPJ Data Science (4 papers)PLoS ONE (3 papers)ACM Transactions on Multimedia Computing Communications and Applications (3 papers)ACM Transactions on Knowledge Discovery from Data (3 papers)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Yu‐Ru Lin
169 papers receiving 3.1k citations
Peers
Comparison fields: 5 of 162
- Computational Mathematics 83
- Statistical and Nonlinear Physics 1.2k
- Transportation 308
- Communication 313
- Computer Vision and Pattern Recognition 751
Countries citing papers authored by Yu‐Ru Lin
This map shows the geographic impact of Yu‐Ru Lin'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 Yu‐Ru Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Ru Lin more than expected).
Fields of papers citing papers by Yu‐Ru Lin
This network shows the impact of papers produced by Yu‐Ru Lin. 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 Yu‐Ru Lin. The network helps show where Yu‐Ru Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Yu‐Ru Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 182 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 258 | |
| 2 | 2009 | 210 | |
| 3 | 2012 | 181 | |
| 4 | 2009 | 148 | |
| 5 | 2007 | 147 | |
| 6 | 2014 | 136 | |
| 7 | 2012 | 133 | |
| 8 | 2015 | 113 | |
| 9 | 2019 | 85 | |
| 10 | 2012 | 81 | |
| 11 | 2017 | 75 | |
| 12 | 2015 | 61 | |
| 13 | Discovery of Blog Communities based on Mutual Awareness | 2006 | 54 |
| 14 | 2014 | 53 | |
| 15 | 2014 | 49 | |
| 16 | 2020 | 49 | |
| 17 | 2007 | 46 | |
| 18 | 2015 | 41 | |
| 19 | 2015 | 37 | |
| 20 | 2013 | 36 |
About Yu‐Ru Lin
Yu‐Ru Lin is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Sociology and Political Science, Communication and Computer Vision and Pattern Recognition, having authored 182 papers that have together received 3.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (51 papers), Opinion Dynamics and Social Influence (29 papers), Social Media and Politics (21 papers), Data Visualization and Analytics (20 papers), Misinformation and Its Impacts (15 papers), Human Mobility and Location-Based Analysis (13 papers), Topic Modeling (9 papers) and Disaster Management and Resilience (8 papers). The work is most often cited by research in Computational Mathematics (83 citations), Statistical and Nonlinear Physics (1.2k citations), Transportation (308 citations), Communication (313 citations) and Computer Vision and Pattern Recognition (751 citations). Yu‐Ru Lin has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Hari Sundaram, Yün Chi, Belle L. Tseng, Nan Cao, Shenghuo Zhu, Lada A. Adamic, Drew Margolin, Xidao Wen, David Lazer and Aisling Kelliher. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, EPJ Data Science, PLoS ONE, ACM Transactions on Multimedia Computing Communications and Applications and ACM Transactions on Knowledge Discovery from Data.
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.