congress_committees — US Congress committee memberships (1993-2017)

Description

Bipartite networks of members of the US Congress and the congressional committees they were assigned to, from the 103rd Congress (1993) to 2017. The data derive from the committee assignment records compiled by Charles Stewart III and Jonathan Woon, which record the membership of all committees of each chamber in each Congress, with dates of assignment and termination. Each committee node corresponds to the membership of one committee during one Congress (so the same committee appears once per Congress), and is connected to the legislators assigned to it during that Congress. A legislator listed more than once for the same committee in the source data is connected to it only once. Committee names and Congress numbers are not included.

house: committees of the House of Representatives and their members.
senate: committees of the Senate and their members.

The networks have the following properties:

is_committee: whether the node is a committee (in a given Congress), otherwise a legislator.
Legislator nodes: name, the name of the legislator; party, the political party of the legislator, "Democrat" or "Republican" (the source data only distinguish these two parties).

Tags

Political Social Governance Affiliation Unweighted Metadata

Citation

C. Stewart III, J. Woon, "Congressional Committee Assignments, 103rd to 114th Congresses, 1993-2017: House" and "...: Senate" (2017) web.mit.edu
P. S. Chodrow, N. Veldt, A. R. Benson, "Generative hypergraph clustering: From blockmodels to modularity." Science Advances 7(28), eabh1303 (2021) 10.1126/sciadv.abh1303 Sci-Hub

Upstream URL OK

https://www.cs.cornell.edu/~arb/data/house-committees/
https://www.cs.cornell.edu/~arb/data/senate-committees/

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
house	1,631	11,843	14.52	15.60	26.26	7.16	-0.63	0.00	8	1.00	Undirected	Bipartite	is_committee name party		22 KiB	44 KiB	43 KiB	44 KiB
senate	597	5,408	18.12	11.38	24.01	19.96	-0.21	0.00	6	1.00	Undirected	Bipartite	is_committee name party		9 KiB	16 KiB	16 KiB	17 KiB