๐Ÿ“ข We're happy to announce the new release of MultilayerGraphs.jl (v1.1) ๐ŸŽ‰!

Interested in multilayer network science in @JuliaLanguage?

Read the following ๐Ÿงต summarising the main features of the package by @ClaudioMoroni and @PietroMonticone.

๐Ÿ“ฆ Repository: https://github.com/JuliaGraphs/MultilayerGraphs.jl

๐Ÿ“„ Documentation: https://juliagraphs.org/MultilayerGraphs.jl

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GitHub - JuliaGraphs/MultilayerGraphs.jl: A Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs.

A Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. - GitHub - JuliaGraphs/MultilayerGraphs.jl: A Julia package for the creati...

GitHub

MultilayerGraphs.jl is a #JuliaLang package for the creation, manipulation and analysis of multilayer graphs.

A multilayer graph consists of multiple subgraphs called "layers" which can be interconnected through bipartite graphs called "interlayers".

#JuliaLang #JuliaPackages #GraphMastodon #MultilayerGraphs #NetworkScience #DataScience #FOSS

@julialang @networkscience

Several theoretical frameworks have been proposed to formally represent #MultilayerNetworks.

Here are some of the main theoretical references:

1. De Domenico et al. (2013) https://doi.org/10.1103/PhysRevX.3.041022;
2. Kivelรค et al. (2014) https://doi.org/10.1093/comnet/cnu016;
3. Aleta and Moreno (2019) https://doi.org/10.1146/annurev-conmatphys-031218-013259;
4. Bianconi (2018) https://doi.org/10.1093/oso/9780198753919.001.0001;
5. Cozzo et al. (2018) https://doi.org/10.1007/978-3-319-92255-3;
6. Artime et al. (2022) https://doi.org/10.1017/9781009085809;
7. De Domenico (2022) https://doi.org/10.1007/978-3-030-75718-2.

Mathematical Formulation of Multilayer Networks

A ``monoplex'' network, like a Facebook-based social network, can be represented by a set of nodes (people) linked by their Facebook connections (interactions). But real-world networks can be ``multiplex,'' with multiple types of interactions and where one type of interaction can influence another. A unifying framework for describing ``multiplex'' networks has been missing so far. Deftly employing the concept of tensors, theorists now present such a framework that will power studies of ``multiplex'' networks across many scientific disciplines.

Physical Review X

#MultilayerGraphs have been adopted to model the structure and dynamics of a wide spectrum of high-dimensional, multi-scale, time-dependent #ComplexSystems including physical, chemical, biological, neuronal, socio-technical, epidemiological, ecological and economic networks.

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@julialang
@networkscience

Here are some of the main applied references:

1. Cozzo et al. (2013) https://doi.org/10.1103/physreve.88.050801;
2. Estrada and Gomez-Gardenes (2014) https://doi.org/10.1103/physreve.89.042819;
3. DeDomenico et al. (2016) https://doi.org/10.1038/nphys3865;
4. Amato et al. (2017) https://doi.org/10.1038/s41598-017-06933-2;
5. DeDomenico (2017) https://doi.org/10.1093/gigascience/gix004;
6. Timteo et al. (2018) https://doi.org/10.1038/s41467-017-02658-y; s
7. Aleta et al. (2020) https://doi.org/10.1038/s41562-020-0931-9;
8. Aleta et al. (2022) https://doi.org/10.1073/pnas.2112182119.

Contact-based social contagion in multiplex networks

We develop a theoretical framework for the study of epidemiclike social contagion in large scale social systems. We consider the most general setting in which different communication platforms or categories form multiplex networks. Specifically, we propose a contact-based information spreading model, and show that the critical point of the multiplex system associated with the active phase is determined by the layer whose contact probability matrix has the largest eigenvalue. The framework is applied to a number of different situations, including a real multiplex system. Finally, we also show that when the system through which information is disseminating is inherently multiplex, working with the graph that results from the aggregation of the different layers is inaccurate.

Physical Review E

Since the previous version of #MultilayerGraphs we have:

โœ… integrated the package within the #JuliaGraphs ecosystem to guarantee methodological consistency and enrich the variety of possible graph structures underlying layers and interlayers https://github.com/JuliaGraphs;

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@julialang
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JuliaGraphs

Graph modeling and analysis packages for the Julia programming language - JuliaGraphs

GitHub