Twitter Interaction Network for the US Congress
Dataset information
This network represents the Twitter interaction network for the 117th 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{fink2023centrality,
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{fink2023twitter,
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}
}
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