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20242026
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physics.soc-ph2026

Reproducing the first and second moments of empirical degree distributions

Mattia Marzi, Francesca Giuffrida, Diego Garlaschelli +1

The study of probabilistic models for the analysis of complex networks represents a flourishing research field. Among the former, Exponential Random Graphs (ERGs) have gained incre…

physics.soc-ph2024

Assessing frustration in real-world signed networks: a statistical theory of balance

Anna Gallo, Diego Garlaschelli, Tiziano Squartini

According to the so-called strong version of structural balance theory, actors in signed social networks avoid establishing triads with an odd number of negative links. Generalisin…

physics.soc-ph2024

Inferring firm-level supply chain networks with realistic systemic risk from industry sector-level data

Massimiliano Fessina, Giulio Cimini, Tiziano Squartini +3

Production networks constitute the backbone of every economic system. They are inherently fragile as several recent crises clearly highlighted. Estimating the system-wide consequen…

physics.soc-ph2024

Patterns of link reciprocity in directed, signed networks

Anna Gallo, Fabio Saracco, Renaud Lambiotte +2

Most of the analyses concerning signed networks have focused on the balance theory, hence identifying frustration with undirected, triadic motifs having an odd number of negative e…

physics.soc-ph2024

Testing structural balance theories in heterogeneous signed networks

Anna Gallo, Diego Garlaschelli, Renaud Lambiotte +2

The abundance of data about social relationships allows the human behavior to be analyzed as any other natural phenomenon. Here we focus on balance theory, stating that social acto…