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Reposted by Marco Mancastroppa

Conference on Complex Systems @css-conference.bsky.social · Sep 1

The conference is officially underway – here are some moments from the opening session.

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

Our work opens several perspectives, from the generation of synthetic realistic hypergraphs describing contexts where data collection is difficult to a deeper understanding of dynamical processes on temporal hypergraphs. 8/8

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

Finally, we illustrate the flexibility of the model, which can generate synthetic hypergraphs with tunable properties: as an example, we generate ”hybrid” temporal hypergraphs, which mix properties of different empirical datasets, and artificial hypergraphs with specifically tuned properties. 7/8

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

We also showcase the possibility to use the resulting synthetic data in simulations of higher-order contagion dynamics, comparing the outcome of such process on original and surrogate datasets. 6/8

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

We first show that the EATH model can generate surrogate hypergraphs of several empirical datasets of face-to-face interactions, mimicking temporal and topological properties at the node and hyperedge level. 5/8

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

We present a new model, the Emerging Activity Temporal Hypergraph (EATH), which can create synthetic time-varying hypergraphs. Each node has an independent activity dynamics, the system activity emerges from it, with temporal group interactions resulting from activity and memory mechanisms. 4/8

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

The corresponding datasets are often incomplete and/or limited in size and duration, and surrogate time-varying hypergraphs constitute interesting substitutions, especially to understand dynamical processes. [ journals.plos.org/ploscompbiol... ] 3/8

Preserving friendships in school contacts: An algorithm to construct synthetic temporal networks for epidemic modelling

Author summary Face-to-face contacts occur between individuals throughout day-to-day activities. These contacts form a network of opportunities for the spread of diseases, such as COVID-19 or influenz...

journals.plos.org

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

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-order and temporal nature of the interactions. [ www.nature.com/articles/s41... ] 2/8

The temporal dynamics of group interactions in higher-order social networks - Nature Communications

The structure and dynamics of many social systems where human interactions involve communities can be described by higher-order networks. The authors propose a hypergraph-based model that describes ho...

www.nature.com

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Jul 3

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?

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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

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Reposted by Marco Mancastroppa

Conference on Complex Systems @css-conference.bsky.social · Jun 11

Delighted to announce the #CCS25 Scientific Dissemination Event!
🌐Free public event in italian called "La complessità è semplice?"
📅 Wednesday, September 3rd, 20:30
📍Teatro dei Rinnovati in the Palazzo Pubblico of Siena
🔗 ccs25.cssociety.org/public-disse...

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Reposted by Marco Mancastroppa

Nicholas Landry @nwlandry.bsky.social · Jun 3

@xgi.bsky.social in the wild 👀

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Reposted by Marco Mancastroppa

Nicholas Landry @nwlandry.bsky.social · Jun 3

Cosimo giving a compelling overview of his pairwise and higher-order network comparison measures

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Reposted by Marco Mancastroppa

Nicholas Landry @nwlandry.bsky.social · Jun 3

@beyondtheedge.network student Cosimo Agostinelli presenting higher-order dissimilarity measures as a way to compare temporal snapshots, empirical data to synthetic null models, etc.

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Reposted by Marco Mancastroppa

Nicholas Landry @nwlandry.bsky.social · Jun 3

Very nice higher-order generative model to try and reproduce the empirical dynamics

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Reposted by Marco Mancastroppa

Nicholas Landry @nwlandry.bsky.social · Jun 3

The hypercoreness ranking correlation between two timestamps is strongly dependent on the timescale (negative correlations for long enough time gap)

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Reposted by Marco Mancastroppa

Nicholas Landry @nwlandry.bsky.social · Jun 3

@marco-mancastroppa.bsky.social talking about temporal evolution from the lens of "hypercores" --- a higher-order extension of the k-core measure for pairwise networks

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Marco Mancastroppa @marco-mancastroppa.bsky.social · May 9

Towards StatPhys2025: interview with
@nicoleyh11.bsky.social
(University of Maryland) by Franco Bagnoli (Dept. Physics and Astronomy, University of Florence & Caffè-Scienza).

youtu.be/oyIJTOGSmZE

Interview with Nicole Yunger Halpern

YouTube video by fisica di tutti i giorni

youtu.be

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Marco Mancastroppa @marco-mancastroppa.bsky.social · May 7

Towards StatPhys2025: interview with @zdeborova.bsky.social (EPFL) by Franco Bagnoli (Dept. Physics and Astronomy, University of Florence & Caffè-Scienza).

youtu.be/hplPGzFSRyo

Interview with Lenka Zdeborova

YouTube video by fisica di tutti i giorni

youtu.be

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 25

Our results highlight the advantages of using higher-order dissimilarity measures over traditional pairwise representations in capturing the full structural complexity of the systems considered. 5/5

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 25

We illustrate the effectiveness of these metrics through clustering experiments on synthetic and empirical higher-order networks, showing their ability to correctly group hypergraphs generated by different models and to distinguish real-world systems coming from different contexts. 4/5

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 25

Here we introduce two novel measures, Hyper NetSimile and Hyperedge Portrait Divergence, specifically designed for comparing hypergraphs, that take explicitly into account the properties of multi-node interactions, using complementary approaches. 3/5

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 25

Networks with higher-order interactions have emerged as a powerful tool to model complex systems. Comparing higher-order systems remains a challenge, since similarity measures designed for pairwise networks fail to capture salient features of hypergraphs. [ epubs.siam.org/doi/10.1137/... ] 2/5

What Are Higher-Order Networks? | SIAM Review

Network-based modeling of complex systems and data using the language of graphs has become an essential topic across a range of different disciplines. Arguably, this graph-based perspective derives it...

epubs.siam.org

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 25

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.
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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...

www.arxiv.org

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Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 6

www.cnrs.fr/fr/presse/le...

Le CNRS soutient le mouvement Stand Up For Science

Le CNRS rappelle son engagement indéfectible pour préserver la liberté académique. L'indépendance des scientifiques et la possibilité de mener une recherche publique fondamentale libre sont des princi...

www.cnrs.fr

Marco Mancastroppa @marco-mancastroppa.bsky.social · Mar 5

Verso StatPhys2025: intervista a @gin-bianconi.bsky.social (Queen Mary University of London) di Franco Bagnoli (Dip. Fisica e Astronomia, UNIFI & Caffè-Scienza).

www.youtube.com/watch?v=VZ_b...

Intervista a Ginestra Bianconi

YouTube video by fisica di tutti i giorni

www.youtube.com

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