Run-Ran Liu

1.6k citations
69 papers · 1.3k · h-index 23

Impact in

Papers in

Run-Ran Liu

65 papers receiving 1.2k citations

Peers

Run-Ran Liu
Comparison fields: 5 of 84
  • Statistical and Nonlinear Physics 664
  • Safety Research 129
  • Information Systems 274
  • Transportation 70
  • Computer Networks and Communications 220
Replace Chun-Xiao Jia with:
Chun-Xiao Jia China
Ingo Scholtes Germany
Hao Guo China
Paulo Shakarian United States
Liming Pan China
Dong Hao China
Giuseppe Mangioni Italy
Christopher Griffin United States
Lourdes Araujo Spain
Run-Ran Liu relative to Chun-Xiao Jia China Chun-Xiao Jia's profile →
Citations per field
00.5×2×3.0×
Chun-Xiao Jia · 1×
Citations per year

Countries citing papers authored by Run-Ran Liu

Since Specialization
Citations

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

Fields of papers citing papers by Run-Ran Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Run-Ran Liu. 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 Run-Ran Liu. The network helps show where Run-Ran Liu may publish in the future.

Co-authors

The 25 scholars most cited alongside Run-Ran Liu, 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 Run-Ran Liu Line = papers co-authored together Run-Ran Liu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Accurate and diverse recommendations via eliminating redundant correlations
2010110
2 201194
3 200966
4 200864
5 201862
6 201254
7 201639
8 201938
9 201135
10 201433
11 201931
12 202031
13 201330
14 201630
15 201630
16 201028
17 202327
18 201426
19 200926
20 201224

About Run-Ran Liu

Run-Ran Liu is a scholar working on Statistical and Nonlinear Physics, Sociology and Political Science, Genetics, Computer Networks and Communications and Public Health, Environmental and Occupational Health, having authored 69 papers that have together received 1.3k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (42 papers), Opinion Dynamics and Social Influence (32 papers), Evolutionary Game Theory and Cooperation (26 papers), Evolution and Genetic Dynamics (16 papers), Mathematical and Theoretical Epidemiology and Ecology Models (10 papers), Recommender Systems and Techniques (9 papers), Experimental Behavioral Economics Studies (6 papers) and Stochastic processes and statistical mechanics (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (664 citations), Safety Research (129 citations), Information Systems (274 citations), Transportation (70 citations) and Computer Networks and Communications (220 citations). Run-Ran Liu has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Chun-Xiao Jia, Bing-Hong Wang, Ming Li, Tao Zhou, Ying‐Cheng Lai, Han-Xin Yang, Sun Duo, Zhihai Rong, Zhen Wang and Haifeng Zhang. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Chaos Solitons & Fractals, Europhysics Letters (EPL), Chaos An Interdisciplinary Journal of Nonlinear Science and Complexity.

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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