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        <title>Helping a Friend or Supporting a Cause? Disentangling Active and Passive Cosponsorship in the U.S. Congress</title>
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        <namePart type="given">Giuseppe</namePart>
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    <abstract>In the U.S. Congress, legislators can use active and passive cosponsorship to support bills. We show that these two types of cosponsorship are driven by two different motivations: the backing of political colleagues and the backing of the bill’s content. To this end, we develop an Encoder+RGCN based model that learns legislator representations from bill texts and speech transcripts. These representations predict active and passive cosponsorship with an F1-score of 0.88.Applying our representations to predict voting decisions, we show that they are interpretable and generalize to unseen tasks.</abstract>
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%0 Conference Proceedings
%T Helping a Friend or Supporting a Cause? Disentangling Active and Passive Cosponsorship in the U.S. Congress
%A Russo, Giuseppe
%A Gote, Christoph
%A Brandenberger, Laurence
%A Schlosser, Sophia
%A Schweitzer, Frank
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F russo-etal-2023-helping
%X In the U.S. Congress, legislators can use active and passive cosponsorship to support bills. We show that these two types of cosponsorship are driven by two different motivations: the backing of political colleagues and the backing of the bill’s content. To this end, we develop an Encoder+RGCN based model that learns legislator representations from bill texts and speech transcripts. These representations predict active and passive cosponsorship with an F1-score of 0.88.Applying our representations to predict voting decisions, we show that they are interpretable and generalize to unseen tasks.
%R 10.18653/v1/2023.acl-long.166
%U https://aclanthology.org/2023.acl-long.166
%U https://doi.org/10.18653/v1/2023.acl-long.166
%P 2952-2969

Markdown (Informal)

[Helping a Friend or Supporting a Cause? Disentangling Active and Passive Cosponsorship in the U.S. Congress](https://aclanthology.org/2023.acl-long.166) (Russo et al., ACL 2023)

• Helping a Friend or Supporting a Cause? Disentangling Active and Passive Cosponsorship in the U.S. Congress (Russo et al., ACL 2023)

ACL

• Giuseppe Russo, Christoph Gote, Laurence Brandenberger, Sophia Schlosser, and Frank Schweitzer. 2023. Helping a Friend or Supporting a Cause? Disentangling Active and Passive Cosponsorship in the U.S. Congress. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2952–2969, Toronto, Canada. Association for Computational Linguistics.