This repository contains:
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Multilink_clustering -main program to detect multilink communities in multiplex network
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The auxiliary functions Similarity Sim_Multilink ScoreLinkModularity
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Files from the data repository http://deim.urv.cat/~manlio.dedomenico/data.php on the Florentine Families dataset with the addition of a .m file (readme_florentine) to read the dataset and put it in the format readable by Multilink_clustering
To run the algorithm on this dataset first run readme_florentine and then directly run the Multilink_clustering function
The Multilink_clustering function takes as input:
- a cell A of M sparse undirected adjacency matrices (ordered layers of the multiplex network) ex. A{1} is a N times N adjacency matrix of layer 1
- the z parameter of the Multilink Community Detection algorithm
- the epsilon parameter of the Multilink Community Detection algorithm
- an optional parameter for printing figures on the scorefunction profile (link modularity, the dendrogram and the similarity matrix)
It produces as an output:
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edge list in the form of array links having each element equal to the pair of nodes connected. The n-th multilink is indicated by the couple of values links(n,1) indicating the first node of the multilink links(n,2) indicating the second node of the multilink
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mutlilinks_community is an array attributing to each multilink a community link_community(n) gives the community of the n-th multilinks
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Z dendrogram
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K_partition optimal cut of the dendrogram
This code can be redistributed and/or modified under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed ny the authors in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
If you use this code please cite
[1] R.J. Mondragon, J.Iacovacci, and G. Bianconi, "Multilinks Communities of Multiplex Networks" (2017).
(c) Ginestra Bianconi (g.bianconi@qmul.ac.uk) Raul J. Mondragon (r.j.mondragon@qmul.ac.uk) Jacopo Iacovacci (j.iacovacci@qmul.ac.uk)