Xiaoran Yan

2.9k citations
74 papers · 2.0k · 1 hit paper · h-index 20

Impact in

Papers in

Xiaoran Yan

68 papers receiving 2.0k citations

Xiaoran Yan's Hit Papers

The "Majority Illusion" in Social Networks 2016 · 575 citations
5750+3+6Years since publication100200300400500

Peers

Xiaoran Yan
Comparison fields: 5 of 189
  • Biomaterials 417
  • Statistical and Nonlinear Physics 318
  • Food Science 195
  • Biochemistry 54
  • Cognitive Neuroscience 148
Replace Ye Ye with:
Ye Ye China
Alberto Fernández Spain
Huaping Zhang China
Yafang Li China
Meng Liu China
Xiaoling Jin China
Pushpak Bhattacharyya India
Jiajun Liu China
Karen A. F. Copeland United States
Xiaoran Yan relative to Ye Ye China Ye Ye's profile →
Citations per field
00.5×5×10×14.4×
Ye Ye · 1×
Citations per year

Countries citing papers authored by Xiaoran Yan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoran Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The "Majority Illusion" in Social Networks
Hit paper breakdown →
2016575
2 2021161
3 2022108
4 202388
5 201983
6 202176
7 202270
8 202170
9 201466
10 201861
11 202355
12 202045
13 202243
14 201340
15 201839
16 202138
17 201632
18 202025
19 202324
20 202423

About Xiaoran Yan

Xiaoran Yan is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Biomaterials, Information Systems and Computer Networks and Communications, having authored 74 papers that have together received 2.0k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (16 papers), Advanced Graph Neural Networks (9 papers), Nanocomposite Films for Food Packaging (9 papers), Privacy-Preserving Technologies in Data (7 papers), Opinion Dynamics and Social Influence (7 papers), Recommender Systems and Techniques (7 papers), Photonic and Optical Devices (6 papers) and Plasmonic and Surface Plasmon Research (6 papers). The work is most often cited by research in Biomaterials (417 citations), Statistical and Nonlinear Physics (318 citations), Food Science (195 citations), Biochemistry (54 citations) and Cognitive Neuroscience (148 citations). Xiaoran Yan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Kristina Lerman, Xin-Zeng Wu, Xiangyou Wang, Meng Cheng, Juan Wang, Rongfei Zhang, Yingjun Cui, Peixin Zhao, Yirong Wang and Olaf Sporns. Their work appears in journals such as Synthetic Metals, IEEE Internet of Things Journal, Scientific Reports, Industrial Crops and Products and PeerJ Computer Science.

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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