Journal of Complex Networks

Journal of Complex Networks
Title	Journal of Complex Networks
Discipline	Network science
Publisher	Oxford University Press
Country	United Kingdom
History	2013–present
Frequency	Bimonthly
Issn	2051-1310

Journal of Complex Networks is a peer-reviewed scientific periodical dedicated to research on networks and complex systems. It publishes original research on theoretical, computational, and empirical studies spanning mathematics, physics, computer science, and interdisciplinary applications. The journal serves as a venue for contributions that connect foundational work by figures and institutions across network science, statistical mechanics, graph theory, and applied fields.

History

The journal was launched in 2013 by Oxford University Press with editorial leadership drawn from research groups affiliated with University of Oxford, Imperial College London, and Massachusetts Institute of Technology. Early editorial board members included scholars associated with Santa Fe Institute, Princeton University, and California Institute of Technology, reflecting ties to networks research advanced at Los Alamos National Laboratory and Bell Labs. The founding period coincided with growing interdisciplinary interest inspired by landmark works from authors at Cornell University, University of California, Berkeley, and Stanford University. Over successive editorial terms the journal attracted submissions from scholars linked to ETH Zurich, Max Planck Society, CNRS, and Tsinghua University, consolidating its profile alongside contemporaneous outlets such as Nature Communications, Physical Review E, and Proceedings of the National Academy of Sciences.

Scope and Topics

The journal's scope covers mathematical formalisms, algorithmic methods, and empirical investigations relevant to networks studied by teams at Harvard University, Columbia University, and New York University. Topics include network topology and dynamics, community detection, percolation, synchronization, spreading processes, and multilayer networks—areas developed through research programs at Los Alamos National Laboratory, Argonne National Laboratory, and Lawrence Berkeley National Laboratory. Applications emphasized include biological networks researched at Harvard Medical School, Salk Institute, and European Molecular Biology Laboratory; technological networks tied to work at Google, Facebook, and Cisco Systems; and social networks reflecting studies from University of Oxford, London School of Economics, and Yale University. The journal also addresses methodological advances in network inference, Bayesian modeling, and machine learning as practiced at DeepMind, Microsoft Research, and IBM Research.

Editorial Structure and Publication Process

The editorial structure features an editor-in-chief supported by associate editors and an international editorial board with members from institutions such as University of Cambridge, University of Chicago, University of Toronto, Peking University, and Seoul National University. Submissions undergo initial editorial screening, single- or double-blind peer review, and iterative revision—procedures similar to those at IEEE Transactions on Network Science and Engineering and SIAM Journal on Applied Mathematics. The journal publishes research articles, review papers, and brief communications, and it coordinates special issues guest-edited by experts affiliated with Santa Fe Institute, Institute for Advanced Study, and Kavli Institute for Theoretical Physics. Editorial policies align with ethical guidelines promoted by organizations like Committee on Publication Ethics and professional societies such as American Physical Society and Association for Computing Machinery.

Abstracting and Indexing

The journal is indexed in major bibliographic services used by researchers at Clarivate Analytics, Scopus, and MathSciNet. Abstracting coverage includes databases run by EBSCO Information Services and ProQuest, and citation tracking appears in platforms operated by Google Scholar, Web of Science, and Dimensions. Institutional repositories and discovery services at JSTOR-partnered libraries, national libraries such as the British Library, and university consortia including HathiTrust facilitate access and archiving. The journal's metadata are incorporated into research profiling systems used at University College London and funding agencies like National Science Foundation and European Research Council.

Impact and Reception

The journal established a reputation among communities influenced by seminal authors from Albert-László Barabási's research lineage, Réka Albert's collaborations, and modeling traditions associated with Duncan Watts and Mark Newman—though individual names here represent broader research directions rather than editorial endorsements. Citations from papers affiliated with Princeton University, Columbia University, and ETH Zurich indicate uptake in studies of epidemic modeling, transportation networks, and brain connectivity. It is frequently cited alongside journals such as Chaos: An Interdisciplinary Journal of Nonlinear Science and Journal of Statistical Mechanics: Theory and Experiment in literature reviews and grant proposals submitted to agencies including Wellcome Trust and National Institutes of Health.

Notable Articles and Special Issues

Notable contributions include methodological advances in multilayer network theory, community detection benchmarks, and dynamics on temporal graphs authored by researchers from Imperial College London, University of Michigan, and Tokyo Institute of Technology. Special issues have focused on topics coordinated with centers such as Center for Complex Network Research, Complexity Science Hub Vienna, and consortiums involving European Commission-funded projects. High-impact articles often intersect with empirical programs at Broad Institute, Allen Institute for Brain Science, and field studies connected to World Health Organization modeling collaborations.

Category:Academic journals Category:Network science journals