ceo_club — CEO Club Memberships

Description

A bipartite network of the memberships of 26 chief executive officers (CEOs) of corporations in the Minneapolis–St. Paul metropolitan area in 15 organizations (labeled as clubs in the data), collected by Galaskiewicz (1985) for his study of corporate philanthropy, and published by Wasserman and Faust (1994) as a subset of a larger data set that is not publicly available. The data are from Cory Brunson's bitriad R package (data set minneapolis1970s, built from the CEOclubsAM matrix of the Bioconductor SNAData package). The CEOs and organizations are anonymous.

Nodes are CEOs and organizations, and an edge connects a CEO to an organization of which they are a member.

The network has the following properties:

Nodes: name, the anonymous label of the CEO (CEO1 to CEO26) or the organization (Club1 to Club15); is_organization, whether the node is an organization.

Tags

Social Affiliation Unweighted

Citation

J. Galaskiewicz, "Social Organization of an Urban Grants Economy: A Study of Business Philanthropy and Nonprofit Organizations." Academic Press (1985) 10.1016/c2013-0-10698-8 Sci-Hub
S. Wasserman, K. Faust, "Social Network Analysis: Methods and Applications." Cambridge University Press (1994) 10.1017/cbo9780511815478 Sci-Hub
K. Faust, "Centrality in affiliation networks." Social Networks 19(2), 157-191 (1997) 10.1016/s0378-8733(96)00300-0 Sci-Hub

Upstream URL OK

https://github.com/corybrunson/bitriad

Upstream license

GNU General Public License v2 (bitriad R package), https://www.gnu.org/licenses/old-licenses/gpl-2.0.html

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
ceo_club	41	98	4.78	3.45	5.06	3.62	-0.31	0.00	5	1.00	Undirected	Bipartite	name is_organization		2 KiB	2 KiB	2 KiB	2 KiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.