multinet (version 4.0)

multinet.predefined: Loading predefined multilayer networks

Description

Creates predefined multilayer networks from the literature.

• ml_empty returns an empty multilayer network, not containing any actor, layer, node or edge.

• ml_aucs returns the AUCS multiplex network described in Rossi and Magnani, 2015. "Towards effective visual analytics on multiplex networks". Chaos, Solitons and Fractals. Elsevier.

• ml_bankwiring returns Padgett's Florentine Families multiplex network.

• ml_florentine returns Padgett's Florentine Families multiplex network.

• ml_monastery returns Sampson's monastery multiplex network.

• ml_tailorshop returns Kapferer's' tailorshop multiplex network.

• ml_toy returns the toy network used as a running example in Dickison, Magnani and Rossi. "Multilayer Social Networks". Cambridge University Press.

Usage

ml_empty(name="")
ml_aucs()
ml_bankwiring()
ml_florentine()
ml_monastery()
ml_tailorshop()
ml_toy()

Arguments

name

The name of the new multilayer network.

Value

All these functions return a multilayer network.

References

• Rossi, Luca, and Magnani, Matteo (2015). Towards effective visual analytics on multiplex and multilayer networks. Chaos, Solitons and Fractals, 72, 68-76. (for ml_aucs()).

• Padgett, John F., and McLean, Paul D. (2006). Organizational Invention and Elite Transformation: The Birth of Partnership Systems in Renaissance Florence. American Journal of Sociology, 111(5), 1463-1568. (for ml_florentine()).

• Breiger, R. and Boorman, S. and Arabic, P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12 (for ml_monastery() and ml_bankwiring() - these authors prepared the datasets, see multilayer.it.uu.se/datasets.html for references to the data collectors).

• Kapferer, Bruce (1972). Strategy and Transaction in an African Factory: African Workers and Indian Management in a Zambian Town. Manchester University Press (for ml_tailorshop()).

See Also

multinet.IO, multinet.generation

Examples

# NOT RUN {
empty <- ml_empty("new network")
aucs <- ml_aucs()
bankwiring <- ml_bankwiring()
florentine <- ml_florentine()
monastery <- ml_monastery()
tailorshop <- ml_tailorshop()
# }