US biomedical agency no longer considers policymakers as ‘mission relevant’, leaving dozens of grants in limbo.

Extracting higher-order structures from multivariate data has become an area of intensive study in complex systems science, as these multipartite interactions can reveal insights into fundamental feat...

Despite raising concerns about the mental health effects associated with the usage of TikTok, little is known about how related content is framed by creators and received by audiences. We collect the ...

The ability of self-organizing systems to display emergent, adaptive capabilities is a fundamental feature of biological life. Understanding the mechanisms by which cells co-ordinate at the micro-scal...

SFI External Professor Laurent Hébert-Dufresne (University of Vermont) is the 2026 recipient of the Erdős-Rényi Prize, the top honor for early-career researchers working in network science.

Inferring higher-order interaction structure from observations of dynamics is a central challenge in complex systems, particularly when data are scarce, noisy, or concentrated in lower-dimensional reg...

An embedding-based disruption measure not only robustly captures disruptive works but also reveals simultaneous discoveries.

Large-scale networks have been instrumental in shaping how we think about social systems, and have undergirded many foundational results in mathematical epidemiology, computational social science, and...

Extracting higher-order structures from multivariate data has become an area of intensive study in complex systems science, as these multipartite interactions can reveal insights into fundamental feat...

HIF: The hypergraph interchange format for higher-order networks - Volume 13

Signed networks provide a principled framework for representing systems in which interactions are not merely present or absent but qualitatively distinct: friendly or antagonistic, supportive or confl...

Author summary The problem of understanding when a set of interacting components of a complex systems produce behavior that is “greater than the sum of their parts" is foundational in many areas of mo...

Most networks encountered in nature, society, and technology have weighted edges, representing the strength of the interaction/association between their vertices. Randomizing the structure of a networ...

In the 21st century, many of the crucial scientific and technical issues facing humanity can be understood as problems associated with understanding, …

Negative ties highlight hidden extremes in social media polarization - Volume 13

Percolation frameworks have been used to characterize the robustness of infrastructural networks. Here, authors introduce a percolation-based framework to study resource consumption and network effect...

Many empirical systems contain complex interactions of arbitrary size, representing, for example, chemical reactions, social groups, co-authorship relationships, and ecological dependencies. These int...

Bridging Minds, Behavior, and Society through Network Science

Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partn...

Neovim: for scientists. Contribute to thosvarley/nvim-lab development by creating an account on GitHub.

We introduce a dynamic percolation model aimed at describing the consumption, and eventual exhaustion, of resources in transportation networks. In the model, rational agents progressively consume the ...