Document Type

Article

Publication Title

Data in Brief

Abstract

We present a social network dataset based on interactions between members of the 117th United States Congress between Feb. 9, 2022, and June 9, 2022. The dataset takes the form of a directed, weighted network in which the edge weights are empirically obtained “probabilities of influence” between all pairs of Congresspeople. Twitter's application programming interface (API) V2 was used to determine the number of times each member of Congress retweeted, quote tweeted, replied to, or mentioned other Congressional members, and the probability of influence was found by normalizing the summed influence by the number of tweets issued by each Congressperson. This network may be of particular interest to the study of information diffusion within social networks.

DOI

https://doi.org/10.1016/j.dib.2023.109521

Publication Date

10-2023

Comments

This article describes the development of a dataset used for the following article:  Fink, Christian G., Kelly Fullin, Guillermo Gutierrez, et al. 2023. “A Centrality Measure for Quantifying Spread on Weighted, Directed Networks.” Physica A: Statistical Mechanics and Its Applications 626 (September): 129083. https://doi.org/10.1016/j.physa.2023.129083.

The dataset can be found hosted on the Gonzaga IR as well as Zenodo and GitHub.

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