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Fernando Diaz-Diaz

@fernandodiazdiaz.bsky.social

Physicist by training, mathematician by work. Assistant Prof. at the University Carlos III (Madrid). Currently exploring the mathematical properties of signed networks. Also interested in statistics, international relations, and mathematical finance.

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Complexity Digest@cxdig.bsky.social · 8mo ago

Signed Networks: theory, methods, and applications

Signed Networks: theory, methods, and applications

Fernando Diaz-Diaz, Elena Candellone, Miguel A. Gonzalez-Casado, Emma Fraxanet, Antoine Vendeville, Irene Ferri, Andreia Sofia Teixeira 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 conflicting, excitatory or inhibitory. This polarity reshapes how we think about structure and dynamics in complex systems: a negative tie is not simply a missing positive one but a constraint that generates tension, and possibly asymmetry. Across disciplines, from sociology to neuroscience and machine learning, signed networks provide a shared language to formalise duality, balance, and opposition as integral components of system behaviour. This review provides a comprehensive and foundational summary of signed network theory. It formalises the mathematical principles of signed graphs and surveys signed-network-specific measures, including signed degree distributions, clustering, centralities, motifs, and Laplacians. It revisits balance theory, tracing its cognitive and structural formulations and their connections to frustration. Structural aspects of signed networks are examined, analysing key topics such as null models, node embeddings, sign prediction, and community detection. Subsequent sections address dynamical processes on and of signed networks, such as opinion dynamics, contagion models, and data-driven approaches for studying evolving networks. Practical challenges in constructing, inferring and validating signed data from real-world systems are also highlighted, and we offer an overview of currently available datasets. We also address common pitfalls and challenges that arise when modelling or analysing signed data. Overall, this review integrates theoretical foundations, methodological approaches, and cross-domain examples, providing a structured entry point and a reference framework for researchers interested in the study of signed networks in complex systems. Read the full article at: arxiv.org

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Andreia Sofia Teixeira@asteixeira.bsky.social · 8mo ago

Our team just released a comprehensive and accessible review of Signed Networks — two years in the making! Theory, methods, applications, all in one place. Feedback welcome. arxiv.org/abs/2511.17247

Signed Networks: theory, methods, and applications

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...

arxiv.org

FisEs Joven '26@fisesjoven.bsky.social · 10mo ago

¡Comienza la cuenta atrás para la IV edición de FisEs Joven! Este encuentro reúne a jóvenes investigadores en física estadística y áreas afines, fomentando el intercambio y la colaboración desde las primeras etapas de la carrera científica. (1/2)

DIFENSC - RSEF@difensc-rsef.bsky.social · 11mo ago

Ayer tuvimos el honor de celebrar el acto de entrega de la I edición de los Premios DIFENSC de tesis doctorales. ✨❄️ ¡Enhorabuena de nuevo a los ganadores Guillermo Barrios Morales y Jorge Tabanera Bravo! 🏅 Gracias a la fundación Sicómoro por hacerlo posible.

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Winter Workshop on Complex Systems@wwcs.bsky.social · 11mo ago

🎤 We’re thrilled to announce our next #WWCS26 speaker: Carmen Cabrera, Lecturer in Geographic Data Science at the University of Liverpool. Camren's research focuses on human mobility patterns across spatiotemporal scales and population groups. We look forward to meeting her at Mallorca ❄️🌍

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