Today, we have celebrated the solemn ceremony for the patron saint of the University of Zaragoza, Saint Braulio. As always, it's a pleasure to share this event with my colleagues, including those from my institute (in the photo).
We link virality and polarization. An ABM calibrated on Brexit and Vaccine debates shows the same parameters that generate cascades also generate polarized opinions. Thanks to @ymoreno.bsky.social and @kleber-ao.com
academic.oup.com/pnasnexus/ar...
New system states introduced with the parameter μ. The same parameterization except for different innovation probability μ can lead to consensus in a homogeneous topology or two polarized communities. On the left, the innovation probability μ = 1. On the right, μ = 0.1.
Social media sites can bring people together or push them further apart. A modeling study shows how small changes in posting or recommendation rules can flip a system from consensus to polarization. In PNAS Nexus: https://ow.ly/hLrY50Y3KPk
they can amplify uncooperative behavior, and iv) overall, the interplay between network topology and reputation shapes whether cooperation thrives or collapses.
Kudos to my co-authors Chunpeng Du, Fei Fang, Alfonso de Miguel-Arribas, Yikang Lu, Yanan Wang, and Xin Pan. (4/4)
ii) direct reputation matters the most: timely, first-hand information helps individuals identify good partners & avoid exploitative ones; iii) group structure plays a double role: in supportive environments, higher-order interactions reinforce cooperation; in competitive ones 3/
Reputation isn't assigned to individuals alone, but to relationships -capturing both direct experience (“how you behaved with me”) & indirect information (“what others say about you”). We show that i) reputation can strongly boost cooperation, even in difficult social dilemmas 2/
New paper out, “Edge-based reputation promotes cooperation in simplicial complexes,” (arxiv.org/abs/2511.22234). Here, we take a step forward by introducing a new reputation mechanism that operates in group contexts, not just pairwise ones. (1/4)
Cosnet Lab Nov 2025, welcoming its new members.
Our findings underscore the crucial role of interlayer link directionality in shaping the emergent behavior of multiplex systems, with potential implications for the design and control of such systems. Kudos to my co-authors: Mateo Bouchet, Alex Tejedor and Xiangrong Wang. (4/4)
In this regime, diffusion becomes dynamically arrested due to interlayer asymmetry, fragmenting the system into disconnected dynamical components & preventing it from converging to equilibrium. We also show that this transition can occur in synthetic and real-world systems 3/4
Previous works showed that directionality within layers can enhance diffusion (e.g., superdiffusion & prime regime). Now, we demonstrate analytically and numerically that asymmetric interlayer links can both reproduce these regimes and, remarkably, lead to a novel phenomenon. 2/4
Now out: "Directionality-induced jamming in multiplex networks" (arxiv.org/abs/2510.22634). We uncover a previously unreported diffusion regime, termed directionality-induced jamming, in multiplex networks that arises solely from the directionality of interlayer couplings. (1/4)
Our findings underscore the crucial role of interlayer link directionality in shaping the emergent behavior of multiplex systems, with potential implications for the design and control of such systems. Kudos to my co-authors: Mateo Bouchet, Alex Tejedor and Xiangrong Wang. (4/4)
In this regime, diffusion becomes dynamically arrested due to interlayer asymmetry, fragmenting the system into disconnected dynamical components & preventing it from converging to equilibrium. We also show that this transition can occur in synthetic and real-world systems (3/4)
Previous works showed that directionality within layers can enhance diffusion (e.g., superdiffusion & prime regime). Now, we demonstrate analytically and numerically that asymmetric interlayer links can both reproduce these regimes and, remarkably, lead to a novel phenomenon. (2/4)
🚀 New preprint alert!
“Advancing coupled behavioural-epidemic models: An interdisciplinary framework for the collection of empirical data”
🔗 www.medrxiv.org/content/10.1...
1/6
In just about a week, the season's first NetSci Colloquium will happen. And we're starting with a bang . . . with none other than Iain Couzin talking about Collective Behavior in Animal Groups. September 24, 10 AM ET. Register here to get a Zoom link: iu.zoom.us/webinar/regi...
Channel your excitement about network science to engage and educate the public!
The deadline for our annual educational video competition is two weeks away. bit.ly/nss-videos
This work took more time & effort than expected, but it is finally out for good! 🎉
Big thanks to my collaborators Carlos Gracia Lázaro & @ymoreno.bsky.social — always a real pleasure to work together.
See the full article at: doi.org/10.1016/j.ch...
Shape the Future of Food Systems at CCS 2025!
How can complexity science unlock solutions for sustainable supply chains, food security & climate resilience?
Submit a 1-2 page abstract + figure by 10 July 2025 is.gd/laMmRc
@arifosch.bsky.social | @ymoreno.bsky.social | S. Baum @csh.ac.at
#CCSFrance2025 23/06 18:15: Public keynote conference from @ymoreno.bsky.social on " #SocialDilemmas via Generative Agent-Based Models" supported by the Fondation de Sciences de la Modélisation & CY Initiative
Attend to discover the blend between #ABM and #LLM
➡️ conferences.css-fr.org?page_id=603
Join CCS 2025’s Food Systems Session! Apply complexity science to tackle food security, climate resilience and supply chains.
Submit a 1-2 page abstract + figure by 10 July 2025 is.gd/laMmRc
#ComplexSystems #FoodSystems #CallForPapers
@arifosch.bsky.social @ymoreno.bsky.social S. Baum @csh.ac.at
Now out: "Rumor propagation on hypergraphs" (arxiv.org/abs/2504.19305). We propose a higher-order rumour model incorporating a group-based annihilation mechanism. We run computational experiments to characterise the model's dynamics in synthetic and real systems... 1/5
Our framework demonstrates a scenario for facilitating the representability of deep neural networks through learning the underlying mechanism, which aims to steer applications for predicting complex behavior that learnable physical rules can drive. Kudos to my co-authors! 4/4
We evaluate the performance of our framework in predicting typical critical behavior in spreading dynamics on various synthetic and real-world networks. Our results show that governing rules can be learned effectively and significantly improve prediction accuracy. 3/4
More specifically, the learned governing rules further refine and guide the representative learning of neural networks from a series of dynamic graphs. This combination enables knowledge-based prediction for the critical behavior of dynamical networked systems 2/4
New MS: "Predicting the critical behavior of complex dynamic systems via learning the governing mechanisms" (arxiv.org/abs/2504.09622). We propose a framework to learn the rules that govern the dynamics of a system & apply it to study SIR dynamics & predict critical properties 1/3
Our paper DOCES (Dynamical Opinion Clusters Exploration Suite) is now published in SoftwareX! 📄
DOCES helps model opinion dynamics in social networks, exploring polarization, algorithmic influence, and user behavior.
🔗 Paper: doi.org/10.1016/j.so...
📌 Library on PyPI: pypi.org/project/doces/
📮Last days to send your contributions to #CCS/FR2025-Paris!
Keynotes: @ymoreno.bsky.social , @elsaarcaute.bsky.social , @ElisaThebault, @CamilleRoth, @HughesBersini.
Deadline March 15th
conferences.css-fr.org
Keynotes #CSS/France2025 : Hugues Bersini (UBL), @camcom.bsky.social (EHESS), @ymoreno.bsky.social (BIFI), @elsaarcaute.bsky.social (UCL)
Guests: Benjamin Fagard (CNRS), Agnieszka Rusinowska (CNRS), Guillaume Deffuant (INRAE)
Full program: conferences.css-fr.org?page_id=474