A Euclidean-distance bipartite network model for roll-call voting recovers legislative factions more cleanly than quadratic-utility ideal point models and embeds bills as interpretable anchors.
https://www.cambridge.org/core/ product/identif ier/S0898588X16000110/type/journal_article
1 Pith paper cite this work, alongside 31 external citations. Polarity classification is still indexing.
1
Pith paper citing it
31
external citations · OpenAlex
fields
stat.AP 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Euclidean Ideal Point Estimation From Roll-Call Data via Distance-Based Bipartite Network Models
A Euclidean-distance bipartite network model for roll-call voting recovers legislative factions more cleanly than quadratic-utility ideal point models and embeds bills as interpretable anchors.