U.S. Congress Signed Network Backbones from Co-Sponsorship Data, 1973-2016

Zachary P. Neal's dataset contains signed network backbones for the U.S. House and Senate across multiple sessions from 1973 to 2016. Relationships between congresspeople are inferred from bill co-sponsorship data using the Stochastic Degree Sequence Model. The data is structured as square matrices where cell values indicate positive (1), negative (-1), or no (0) relationships.

Use Cases

• Analyze polarization trends over time based on inferred positive and negative relationships.
• Study legislative collaboration patterns within and across political parties based on co-sponsorship data.
• Model the evolution of the congressional social network across sessions from 1973 to 2016.
• Validate network inference methods like the Stochastic Degree Sequence Model on real-world political data.

Strengths

• Covers a long temporal range from 1973 to 2016, spanning multiple congressional sessions.
• Provides data for both chambers of Congress (House and Senate) separately.
• Relationships are derived using a published methodological framework (Stochastic Degree Sequence Model).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and dataset size are unknown, which may limit suitability assessment.
• Data may reflect temporal and source bias inherent to the co-sponsorship inference method.

Provenance

Source

Zachary P. Neal

Collection Method

Relationships inferred from U.S. Congressional bill co-sponsorship data using the Stochastic Degree Sequence Model.

Time Range

1973-2016

Geography

United States