Twitter Interaction Network for the US Congress

Dataset information

This network represents the Twitter interaction network for the $117$th United States Congress, both House of Representatives and Senate. The base data was collected via the Twitter$$s API, then the empirical transmission probabilities were quantified according to the fraction of times one member retweeted, quote tweeted, replied to$,$ or mentioned another member$$s tweet. See the publication for more details.

Dataset statistics

Directed Yes.

Node features No$.$

Edge features Yes.

Nodes $475$

Edges $13,289$

Source $($citation$)$

C$.$G$.$ Fink, K$.$ Fullin, G$.$ Gutierrez, N$.$ Omodt, S$.$ Zinnecker, G$.$ Sprint, and S$.$ McCulloch: A centrality measure for quantifying spread on weighted, directed networks. Physica A$,2023.$

@article$\{$fink$2023$centrality,

title$=\{$A centrality measure for quantifying spread on weighted, directed networks$\},$

author$=\{$Fink$,$ Christian G and Fullin, Kelly and Gutierrez, Guillermo and Omodt, Nathan and Zinnecker, Sydney and Sprint, Gina and McCulloch, Sean$\},$

journal$=\{$Physica A$\},$

year$=\{2023\}$

$\}$

Dataset Description

C$.$G$.$ Fink, N$.$ Omodt, S$.$ Zinnecker, and G$.$ Sprint: A Congressional Twitter network dataset quantifying pairwise probability of influence. Data in Brief, $2023.$

@article$\{$fink$2023$twitter,

title$=\{$A Congressional Twitter network dataset quantifying pairwise probability of influence$\},$

author$=\{$Fink$,$ Christian G and Omodt, Nathan and Zinnecker, Sydney and Sprint, Gina$\},$

journal$=\{$Data in Brief$\},$

year$=\{2023\}$

$\}$

Files

File Description

congress$\_$network.zip Twitter Interaction Network for the US Congress