Journal of Complex Networks

472 papers and 7.1k indexed citations i.

About

The 472 papers published in Journal of Complex Networks in the last decades have received a total of 7.1k indexed citations. Papers published in Journal of Complex Networks usually cover Statistical and Nonlinear Physics (359 papers), Molecular Biology (75 papers) and Computational Theory and Mathematics (67 papers) specifically the topics of Complex Network Analysis Techniques (350 papers), Opinion Dynamics and Social Influence (183 papers) and Bioinformatics and Genomic Networks (46 papers). The most active scholars publishing in Journal of Complex Networks are Mason A. Porter, Àlex Arenas, Yamir Moreno, James P. Gleeson, Marc Barthélemy, Mikko Kivelä, Matjaž Perc, Mahdi Jalili, Piet Van Mieghem and Rik Sarkar.

In The Last Decade

Fields of papers published in Journal of Complex Networks

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Journal of Complex Networks. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Journal of Complex Networks.

Countries where authors publish in Journal of Complex Networks

Since Specialization
Citations

This map shows the geographic impact of research published in Journal of Complex Networks. 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 papers published in Journal of Complex Networks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Journal of Complex Networks more than expected).

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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