uk_faculty — UK university faculty friendship network (2007)

Description

The personal friendship network among the academic staff of a Faculty of a UK university, consisting of three schools, collected by Nepusz, Petróczi, Négyessy and Bazsó. The ties were obtained from a questionnaire answered by every member of the academic staff, from which the strength of each tie was measured on a scale constructed from several questionnaire items (reported Cronbach's α of 0.91). The edges are directed and weighted by the measured tie strength (the direction of the edges is as in the distributed data; the original publication analyzed the network ignoring directions, and does not detail their meaning). The data were distributed with the R package igraphdata, from which this version was obtained (the network object there is dated March 2007).

The network has the following properties:

Nodes: school, an integer from 1 to 4 identifying the school of the Faculty to which the individual belongs. Values 1, 2 and 3 correspond to the three schools; the value 4 is given to two individuals, which presumably correspond to the two individuals whose school affiliation the authors report as unknown, due to missing information in the questionnaire.
Edges: weight, the strength of the tie, an integer from 1 to 16 (larger values indicate stronger ties).

Tags

Social Offline Weighted Metadata

Citation

T. Nepusz, A. Petróczi, L. Négyessy, F. Bazsó, "Fuzzy communities and the concept of bridgeness in complex networks." Physical Review E 77, 016107 (2008) 10.1103/PhysRevE.77.016107 Sci-Hub

Upstream URL OK

https://github.com/igraph/igraphdata

Upstream license

Creative Commons Attribution-ShareAlike 2.0 UK: England & Wales (CC BY-SA 2.0 UK), https://creativecommons.org/licenses/by-sa/2.0/uk/

Networks

Tip: hover over a column header 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
uk_faculty	81	817	10.09	11.69	18.07	7.01	0.07	0.51	4	1.00	Directed	Unipartite	school	weight	2 KiB	4 KiB	4 KiB	3 KiB