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Marco Mancastroppa

@marco-mancastroppa.bsky.social

Physicist. Postdoc at EPIcx lab, Sorbonne Université, INSERM, Sorbonne Public Health Institute, Sorbonne Université Modeling Outbreaks Center (SUMOC) https://marco-mancastroppa.github.io/

49 Posts107 Follower164 Folgt
Marco Mancastroppa@marco-mancastroppa.bsky.social · 2mo ago

How do group adaptive behaviors influence the emergence of polarization and consensus? Our work on the impact of group adaptation on opinion dynamics is now out in APS Open Science! 🚨 journals.aps.org/apsos/abstra... with Cosimo Agostinelli and @alainbarrat.bsky.social 1/2

Group adaptation drives opinion dynamics in higher-order networks

In modern interconnected societies, opinions and beliefs can quickly spread across large populations, giving rise to collective behaviors such as the adoption of social norms or polarization. The inte...

journals.aps.org

Hang-Hyun Jo@socph.bsky.social · 2mo ago

Our new preprint is out on arXiv: Jiyoung Kang, Hang-Hyun Jo, Naoki Masuda, Quantifying concurrency in event-based temporal network and hypergraph data arxiv.org/abs/2605.24633

Quantifying concurrency in event-based temporal network and hypergraph data

Many social, biological, and technological systems are recorded as sequences of time-stamped interactions. In such systems, concurrency, i.e., the tendency for an individual to participate in multiple...

arxiv.org

Marco Mancastroppa@marco-mancastroppa.bsky.social · 5mo ago

Now out our latest paper on adaptive opinion dynamics! 🚨 w/ Cosimo Agostinelli and @alainbarrat.bsky.social arxiv.org/abs/2602.19684 How do group adaptive behaviors influence the emergence of polarization and consensus? How does group adaptation influence the structure of interactions? 1/6 🧵👇

Group adaptation drives opinion dynamics in higher-order networks

In modern interconnected societies, opinions and beliefs can quickly spread across large populations, giving rise to collective behaviors such as the adoption of social norms or polarization. These ph...

arxiv.org

Marco Mancastroppa@marco-mancastroppa.bsky.social · 6mo ago

Another new preprint on group adaptation! 📣 Great joint work w/ @martonkarsai.bsky.social and @alainbarrat.bsky.social! Can adaptive behaviors driven by group interactions be more effective and less costly than pairwise ones? How do their adaptive mechanisms differ? arxiv.org/abs/2602.05915 🧵 1/7

Higher-order adaptive behaviors outperform pairwise strategies in mitigating contagion dynamics

When exposed to a contagion phenomenon, individuals may respond to the perceived risk of infection by adopting behavioral changes, aiming to reduce their exposure or their risk of infecting others. Th...

arxiv.org

Marco Mancastroppa@marco-mancastroppa.bsky.social · 7mo ago

New preprint out! 📣 Great collaboration w/ @martonkarsai.bsky.social and @alainbarrat.bsky.social! How do adaptive behaviors, triggered by risk perception, affect higher-order contagion processes? What happens to the contagion dynamics and to the phase transition? arxiv.org/abs/2601.05801 🧵1/7

Adaptive behaviors neutralize bistable explosive transitions in higher-order contagion

During contagion phenomena, individuals perceiving a risk of infection commonly adapt their behavior and reduce their exposure. The effects of such adaptive mechanisms have been studied for processes ...

arxiv.org

Marco Mancastroppa@marco-mancastroppa.bsky.social · 9mo ago

The EATH model for realistic hypergraphs generation is now out in Physical Review E! 📣 journals.aps.org/pre/abstract... with @giuliacencetti.bsky.social and @alainbarrat.bsky.social 1/2

Emerging activity temporal hypergraph: A model for generating realistic time-varying hypergraphs

Time-varying group interactions constitute the building blocks of many complex systems. The framework of temporal hypergraphs makes it possible to represent them by taking into account the higher-orde...

journals.aps.org

Marco Mancastroppa@marco-mancastroppa.bsky.social · last yr.

New preprint out! 📣 “Emerging Activity Temporal Hypergraph (EATH), a model for generating realistic time-varying hypergraphs” with @giuliacencetti.bsky.social and @alainbarrat.bsky.social arxiv.org/abs/2507.01124 How can we generate realistic time-varying hypergraphs? 1/8 🧵⬇️

Emerging Activity Temporal Hypergraph (EATH), a model for generating realistic time-varying hypergraphs

Time-varying group interactions constitute the building blocks of many complex systems. The framework of temporal hypergraphs makes it possible to represent them by taking into account the higher-orde...

arxiv.org

Marco Mancastroppa@marco-mancastroppa.bsky.social · last yr.

Now out our new preprint “Higher-order dissimilarity measures for hypergraph comparison”! www.arxiv.org/abs/2503.16959 With Cosimo Agostinelli and @alainbarrat.bsky.social We extend to hypergraphs similarity measures defined previously only on pairwise networks. 🧵⬇️ 1/5

Higher-order dissimilarity measures for hypergraph comparison

In recent years, networks with higher-order interactions have emerged as a powerful tool to model complex systems. Comparing these higher-order systems remains however a challenge. Traditional similar...

arxiv.org