Legislative cosponsorship networks in the US House and Senate

By James H. Fowler. Soc. Networks, 2006

391 citations recorded by the source corpus.

Subfields: Communication, Political Science and International Relations, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/4fca4a2f53e0038436124aeacbebf0e43c8efcaa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

1. Austin R. Benson
2. Jon M. Kleinberg
3. Rediet Abebe
4. Charu C. Aggarwal
5. Jiliang Tang

In Strategy and Management

1. Jon M. Kleinberg

Citations in the corpus

• Graph Neural Networks for Graphs With Heterophily: A Survey (2022, neutral): “Therefore, the research further analyzes its learnable equivariant diffusion operator and demonstrates its superiority in predicting heterophilic node labels on four hypergraphs: Congress [114], Senate [114], Walmart [115], and House [116].”
• Simplicial closure and higher-order link prediction (2018, background): “Congress data [congress-committees (21); congress-bills (22)]: Nodes are members of Congress and a simplex is the set of members in a committee or cosponsoring a bill; the committees dataset spans 1989–2003 and the bills dataset spans 1973–2016.”