Yu‐Ru Lin

5.1k citations
177 papers · 3.2k indexed · h-index 27

Yu‐Ru Lin

161 papers receiving 3.0k citations

Peers

Yu‐Ru Lin
Comparison fields: 5 of 165
  • Computational Mathematics 85
  • Statistical and Nonlinear Physics 1.2k
  • Transportation 309
  • Communication 309
  • Computer Vision and Pattern Recognition 744
Replace Belle L. Tseng with:
Belle L. Tseng United States
Qi He United States
Matthew Richardson United States
Derek Greene Ireland
Yuxiao Dong China
Andreas Hotho Germany
Liangjie Hong United States
Evgeniy Gabrilovich United States
Anna Squicciarini United States
Andrew McCallum United States
Yu‐Ru Lin relative to Belle L. Tseng United States Belle L. Tseng's profile →
Citations per field
00.5×
Belle L. Tseng · 1×
Citations per year

Countries citing papers authored by Yu‐Ru Lin

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network

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.

Border = papers with Yu‐Ru Lin Line = papers co-authored together Yu‐Ru Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20257
3 20250
4 20250
5 20250
6 202411
7 202414
8 20242
9 20231
10 20231
11 202213
12
Tensor Factorization for Student Modeling and Performance Prediction in Unstructured Domain.
201612
13 20169
14 20158
15 201419
16
The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises
201421
17
Spatiotemporal features of human mobility
20121
18 2012131
19
Classification of parallel machine environments under various correlation structures
20064
20
The Splog Detection Task and A Solution Based on Temporal and Link Properties.
20069

About Yu‐Ru Lin

Yu‐Ru Lin is a scholar working on Computational Mathematics, Statistical and Nonlinear Physics and Communication, having authored 177 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), Data Visualization and Analytics (20 papers), Social Media and Politics (20 papers), Misinformation and Its Impacts (14 papers), Human Mobility and Location-Based Analysis (13 papers), Topic Modeling (9 papers) and Advanced Text Analysis Techniques (8 papers). The work is most often cited by research in Computational Mathematics (85 citations), Statistical and Nonlinear Physics (1.2k citations) and Transportation (309 citations). Yu‐Ru Lin has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Hari Sundaram, Belle L. Tseng, Yün Chi, 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, ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Multimedia Computing Communications and Applications and PLoS ONE.

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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