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.
Efficient routing on complex networks
2006476 citationsTao Zhou, Bing-Hong Wang et al.Physical Review Eprofile →
Identifying influential spreaders in complex networks based on gravity formula
2016248 citationsBing-Hong Wang et al.Physica A Statistical Mechanics and its Applicationsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Bing-Hong Wang
Since
Specialization
Citations
This map shows the geographic impact of Bing-Hong Wang'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 Bing-Hong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing-Hong Wang more than expected).
This network shows the impact of papers produced by Bing-Hong Wang. 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 Bing-Hong Wang. The network helps show where Bing-Hong Wang may publish in the future.
Co-authorship network of co-authors of Bing-Hong Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Bing-Hong Wang.
A scholar is included among the top collaborators of Bing-Hong Wang 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 Bing-Hong Wang. Bing-Hong Wang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yan, Xiao-Yong, Xiao-Pu Han, Bing-Hong Wang, & Tao Zhou. (2012). Diversity of Individual Mobility Patterns. arXiv (Cornell University).1 indexed citations
7.
Wang, Bing-Hong. (2012). Review on the Research of Evolutionary Games on Complex Networks. Journal of the University of Shanghai for Science and Technology.1 indexed citations
Zhou, Tao, Ri‐Qi Su, Run-Ran Liu, et al.. (2010). Accurate and diverse recommendations via eliminating redundant correlations. reroDoc Digital Library.104 indexed citations
11.
Liu, Jian-Guo, Tao Zhou, Bing-Hong Wang, Yicheng Zhang, & Qiang Guo. (2010). EFFECTS OF USER'S TASTES ON PERSONALIZED RECOMMENDATION. RePEc: Research Papers in Economics.36 indexed citations
12.
Wang, Bing-Hong. (2010). The Recent Advancements for Traffic Flow Research at USTC.1 indexed citations
13.
Wang, Bing-Hong. (2010). On Spreading Dynamics on Networks.6 indexed citations
14.
Hong, Wei, Xiao-Pu Han, Tao Zhou, & Bing-Hong Wang. (2009). Heavy-tailed statistics in short-message communication. reroDoc Digital Library.72 indexed citations
15.
Wang, Bing-Hong. (2009). Overview of the Evaluated Algorithms for the Personal Recommendation Systems.13 indexed citations
Xiao-Shu, Luo & Bing-Hong Wang. (2004). On dynamics of discrete model based on investment competition. Guanli kexue xuebao.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.