Jun Wu

136 papers receiving 1.9k citations

Peers

Jun Wu
Comparison fields: 5 of 148
  • Statistical and Nonlinear Physics 835
  • Geometry and Topology 200
  • Computer Networks and Communications 475
  • Condensed Matter Physics 142
  • Civil and Structural Engineering 189
Replace Gang Yan with:
Gang Yan China
Dieter Armbruster United States
Lidia A. Braunstein Argentina
Gerald Paul United States
Keren Erez Israel
Shiming Chen China
Mao-Bin Hu China
Yanqing Hu China
Jie Zhou China
Hui‐Jia Li China
Jun Wu relative to Gang Yan China Gang Yan's profile →
Citations per field
00.5×1.5×1.9×
Gang Yan · 1×
Citations per year

Countries citing papers authored by Jun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Wu. 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 Jun Wu. The network helps show where Jun Wu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 155 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011196
2 2010181
3 1999163
4 2015153
5 200781
6
Network Structure Entropy and Its Application to Scale-free Networks
200461
7 201558
8 201642
9 201641
10 201840
11 201234
12 201730
13 201629
14 200728
15 201927
16 201924
17 201522
18 201822
19 201822
20 202122

About Jun Wu

Jun Wu is a scholar working on Statistical and Nonlinear Physics, Geometry and Topology, Computer Networks and Communications, Management Science and Operations Research and Energy Engineering and Power Technology, having authored 155 papers that have together received 2.0k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (59 papers), Opinion Dynamics and Social Influence (35 papers), Graph theory and applications (15 papers), Network Security and Intrusion Detection (13 papers), Auction Theory and Applications (11 papers), Opportunistic and Delay-Tolerant Networks (9 papers), Game Theory and Voting Systems (8 papers) and Optimization and Search Problems (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (835 citations), Geometry and Topology (200 citations), Computer Networks and Communications (475 citations), Condensed Matter Physics (142 citations) and Civil and Structural Engineering (189 citations). Jun Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Hongzhong Deng, Yuejin Tan, Mauricio Barahona, Guansheng Peng, Ye Deng, Suoyi Tan, Yapeng Li, Xin Lü, Yong Li and M. Hamilton. Their work appears in journals such as Chaos An Interdisciplinary Journal of Nonlinear Science, Chinese Physics Letters, Information Processing & Management, Physica A Statistical Mechanics and its Applications and Reliability Engineering & System Safety.

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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