Xiu‐Xiu Zhan

1.2k total citations · 1 hit paper
33 papers, 844 citations indexed

About

Xiu‐Xiu Zhan is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Xiu‐Xiu Zhan has authored 33 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Statistical and Nonlinear Physics, 9 papers in Artificial Intelligence and 5 papers in Molecular Biology. Recurrent topics in Xiu‐Xiu Zhan's work include Complex Network Analysis Techniques (25 papers), Opinion Dynamics and Social Influence (16 papers) and Advanced Graph Neural Networks (9 papers). Xiu‐Xiu Zhan is often cited by papers focused on Complex Network Analysis Techniques (25 papers), Opinion Dynamics and Social Influence (16 papers) and Advanced Graph Neural Networks (9 papers). Xiu‐Xiu Zhan collaborates with scholars based in China, Netherlands and United States. Xiu‐Xiu Zhan's co-authors include Zi‐Ke Zhang, Chuang Liu, Xin Lü, Chuxu Zhang, Yi‐Cheng Zhang, Gui‐Quan Sun, Chuang Liu, Zhen Jin, Ge Zhou and Jonathan J. H. Zhu and has published in prestigious journals such as Scientific Reports, Physics Reports and Expert Systems with Applications.

In The Last Decade

Xiu‐Xiu Zhan

29 papers receiving 811 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Dynamics of information diffusion and its applications on complex networks

2016 346 citations Zi‐Ke Zhang, Xiu‐Xiu Zhan et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiu‐Xiu Zhan China	13	672	144	119	118	115	33	844
Shi‐Min Cai China	18	822 1.2×	154 1.1×	169 1.4×	161 1.4×	165 1.4×	113	1.3k
Zhongyuan Ruan China	15	407 0.6×	106 0.7×	79 0.7×	148 1.3×	96 0.8×	45	702
J. G. Oliveira Portugal	9	779 1.2×	111 0.8×	48 0.4×	62 0.5×	121 1.1×	12	1.1k
Quantong Guo China	11	651 1.0×	150 1.0×	29 0.2×	290 2.5×	100 0.9×	13	835
Shaoting Tang China	14	389 0.6×	190 1.3×	48 0.4×	26 0.2×	82 0.7×	51	581
Zhesi Shen China	15	553 0.8×	107 0.7×	151 1.3×	30 0.3×	110 1.0×	41	981
Liming Pan China	13	664 1.0×	144 1.0×	318 2.7×	56 0.5×	84 0.7×	37	998
Muhua Zheng China	13	382 0.6×	98 0.7×	27 0.2×	77 0.7×	92 0.8×	39	530
Wen-Jie Bai China	9	505 0.8×	52 0.4×	36 0.3×	106 0.9×	144 1.3×	10	621

Countries citing papers authored by Xiu‐Xiu Zhan

Since Specialization

Citations

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

Fields of papers citing papers by Xiu‐Xiu Zhan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiu‐Xiu Zhan. 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 Xiu‐Xiu Zhan. The network helps show where Xiu‐Xiu Zhan may publish in the future.

Co-authorship network of co-authors of Xiu‐Xiu Zhan

This figure shows the co-authorship network connecting the top 25 collaborators of Xiu‐Xiu Zhan. A scholar is included among the top collaborators of Xiu‐Xiu Zhan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiu‐Xiu Zhan. Xiu‐Xiu Zhan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Zhan, Xiu‐Xiu, et al.. (2025). Modeling the coevolution of information diffusion and garbage classification behavior on simplicial complex networks. Chaos Solitons & Fractals. 199. 116672–116672. 1 indexed citations

Zhan, Xiu‐Xiu, et al.. (2025). Temporal modeling and resilience analysis of supply chain networks under cascading failures. Reliability Engineering & System Safety. 266. 111763–111763.

Liu, Xiaoyang, et al.. (2025). GAWF: Influence maximization method based on graph attention weight fusion. International Journal of Modern Physics C. 37(6). 2 indexed citations

Yu, Xiaoyan, et al.. (2025). Locating influential nodes in hypergraphs via fuzzy collective influence. Communications in Nonlinear Science and Numerical Simulation. 142. 108574–108574. 3 indexed citations

Zhan, Xiu‐Xiu, et al.. (2025). EasyHypergraph: an open-source software for fast and memory-saving analysis and learning of higher-order networks. Humanities and Social Sciences Communications. 12(1). 1 indexed citations

Li, Cong, et al.. (2025). ESND: An embedding-based framework for signed network dismantling. Expert Systems with Applications. 289. 128346–128346. 1 indexed citations

Xie, Ming, et al.. (2025). Influence maximization in multilayer networks based on adaptive coupling degree. Chaos An Interdisciplinary Journal of Nonlinear Science. 35(3).

Ke, Qiao, et al.. (2025). Hypergraph dismantling with spectral clustering. Communications in Nonlinear Science and Numerical Simulation. 150. 108975–108975. 1 indexed citations

Zhan, Xiu‐Xiu, et al.. (2025). Measuring and utilizing temporal network dissimilarity. Communications Physics. 8(1). 1 indexed citations

10.

Zhang, Zi‐Ke, et al.. (2024). A hyper-distance-based method for hypernetwork comparison. Chaos An Interdisciplinary Journal of Nonlinear Science. 34(8). 2 indexed citations

11.

Xu, Jin, Jin Xu, Ming Xie, et al.. (2024). IMVis: Visual analytics for influence maximization algorithm evaluation in hypergraphs. Visual Informatics. 8(2). 13–26. 2 indexed citations

12.

Pei, Xin, et al.. (2024). Dynamic modeling and analysis of brucellosis on metapopulation network: Heilongjiang as cases. Chinese Physics B. 34(1). 18904–18904.

13.

Zhan, Xiu‐Xiu, et al.. (2023). Vital node identification in hypergraphs via gravity model. Chaos An Interdisciplinary Journal of Nonlinear Science. 33(1). 13104–13104. 33 indexed citations

14.

Zhan, Xiu‐Xiu, et al.. (2023). Research on Recommendation Algorithms Based on Asymmetric Attention Mechanism Models. 401–408.

15.

Wang, Zhipeng, Xiu‐Xiu Zhan, Chuang Liu, & Zi‐Ke Zhang. (2022). Quantification of network structural dissimilarities based on network embedding. iScience. 25(6). 104446–104446. 5 indexed citations

16.

Zhan, Xiu‐Xiu, et al.. (2021). Temporal Network Prediction and Interpretation. IEEE Transactions on Network Science and Engineering. 9(3). 1215–1224. 12 indexed citations

17.

Zhan, Xiu‐Xiu, Alan Hanjalić, & Huijuan Wang. (2019). Information diffusion backbones in temporal networks. Scientific Reports. 9(1). 6798–6798. 17 indexed citations

18.

Zhan, Xiu‐Xiu, Chuang Liu, Gui‐Quan Sun, & Zi‐Ke Zhang. (2018). Epidemic dynamics on information-driven adaptive networks. Chaos Solitons & Fractals. 108. 196–204. 29 indexed citations

19.

Zhan, Xiu‐Xiu, et al.. (2017). Identifying vital nodes on temporal networks: An edge-based K-shell decomposition. 1402–1407. 8 indexed citations

20.

Zhou, Nan, et al.. (2017). Information diffusion on communication networks based on Big Data analysis. The Electronic Library. 35(4). 745–757. 4 indexed citations

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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