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.
Limits of Predictability in Human Mobility
20102.3k citationsChaoming Song, Nicholas Blumm et al.profile →
Self-similarity of complex networks
20051.0k citationsChaoming Song, Shlomo Havlin et al.profile →
Modelling the scaling properties of human mobility
2010912 citationsChaoming Song, Tal Koren et al.Nature Physicsprofile →
A phase diagram for jammed matter
2008721 citationsChaoming Song, Ping Wang et al.profile →
Quantifying Long-Term Scientific Impact
2013545 citationsDashun Wang, Chaoming Song et al.profile →
Origins of fractality in the growth of complex networks
2006457 citationsChaoming Song, Shlomo Havlin et al.Nature Physicsprofile →
Human mobility, social ties, and link prediction
2011455 citationsDashun Wang, Chaoming Song et al.profile →
Quantifying the evolution of individual scientific impact
2016359 citationsDashun Wang, Chaoming Song et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Chaoming Song'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 Chaoming Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaoming Song more than expected).
This network shows the impact of papers produced by Chaoming Song. 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 Chaoming Song. The network helps show where Chaoming Song may publish in the future.
Co-authorship network of co-authors of Chaoming Song
This figure shows the co-authorship network connecting the top 25 collaborators of Chaoming Song.
A scholar is included among the top collaborators of Chaoming Song 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 Chaoming Song. Chaoming Song is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wang, Dashun, Zhen Wen, Hanghang Tong, et al.. (2012). Information Spreading in Context. Bulletin of the American Physical Society. 2012.4 indexed citations
Song, Chaoming, et al.. (2010). Limits of predictability in human mobility. Bulletin of the American Physical Society. 2010.12 indexed citations
14.
Song, Chaoming, Tal Koren, Pu Wang, & Albert-Ĺaszló Barabási. (2010). Modelling the scaling properties of human mobility. Nature Physics. 6(10). 818–823.912 indexed citations breakdown →
Luo, Lan, Zehui Qu, & Chaoming Song. (2009). Precise transformation of Feistel to SP fuse into LFSR. China Communications. 6(4). 168–171.
17.
Wang, Ping, Chaoming Song, & Hernán A. Makse. (2008). A phase diagram for jammed matter reveals the nature of the random loose and random close packing of spheres. Bulletin of the American Physical Society.1 indexed citations
18.
Wang, Ping, Chaoming Song, Yuliang Jin, & Hernán A. Makse. (2008). Jamming IV: Distribution of volumes and coordination number in jammed matter: mesoscopic ensemble. arXiv (Cornell University).1 indexed citations
Song, Chaoming & Shlomo Havlin. (2005). Fractal growth of complex networks: repulsion between hubs. arXiv (Cornell University).2 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.