physics_collab — Multilayer physicist collaborations (2015)
- Description
Two multilayer coauthorship networks of scientists, assembled by M. De Domenico, A. Lancichinetti, A. Arenas and M. Rosvall. Nodes are scientists (anonymized) and edges are coauthorships, with layers corresponding to research topics:
pierreAuger: coauthorships of internal technical reports of the Pierre Auger Collaboration, which operates an observatory of ultra-high-energy cosmic rays, submitted between 2010 and 2012. Each report was assigned to one or more of 16 layers corresponding to working tasks (neutrinos, detector, enhancements, anisotropy, point source, mass composition, horizontal showers, hybrid reconstruction, spectrum, photons, atmospheric, SD reconstruction, hadronic interactions, exotics, magnetic fields, astrophysical scenarios), according to its keywords and content, with manual disambiguation.arXiv: coauthorships of preprints posted on arXiv up to May 2014 with "networks" in the title or abstract, with 13 layers corresponding to the arXiv categories of the preprints (physics.soc-ph, physics.data-an, physics.bio-ph, math-ph, math.OC, cond-mat.dis-nn, cond-mat.stat-mech, q-bio.MN, q-bio, q-bio.BM, nlin.AO, cs.SI, cs.CV).
The edges are weighted as follows: for each report or preprint with $N > 1$ authors, classified into $L$ layers, a weight $1/[L(N-1)]$ is added to the edge between each pair of its coauthors in each of these layers. Hence, the sum of the weights of the edges of an author over all layers is the number of (multi-author) papers they wrote. Each pair of authors has at most one edge per layer.
The networks have the following properties:
- (Node)
name: empty, since the identities of the authors are not provided. - (Edge)
layer: the layer of the edge, numbered as listed above (see the graph propertylayer_key). - (Edge)
weight: the edge weight, as defined above.
- Tags
- Social Collaboration Weighted Multilayer Projection
- Added
- 2020-08-11
- Citation
-
- M. De Domenico et al., "Identifying modular flows on multilayer networks reveals highly overlapping organization in interconnected systems." Physical Review X 5(1), 011027 (2015). arXiv:1408.2925
- Upstream URL OK
- https://manliodedomenico.com/data.php
- Upstream license
- Open Data Commons Open Database License (ODbL), https://opendatacommons.org/licenses/odbl/
- Networks
-
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv pierreAuger 514 7,153 27.83 29.42 75.46 64.13 0.65 0.86 9 0.92 Undirected Unipartite name weight layer 15 KiB 37 KiB 35 KiB 30 KiB arXiv 14,488 59,026 8.15 13.67 47.00 918.69 0.19 0.35 18 0.61 Undirected Unipartite name weight layer 342 KiB 605 KiB 589 KiB 464 KiB - Ridiculograms*