Papers by Eric Waltenburg

2 papers
Understanding the Language of Political Agreement and Disagreement in Legislative Texts (2020.acl-main)

Copied to clipboard

Challenge: Despite the fact that state-level legislation is rarely discussed, it has a dramatic influence on the everyday life of residents of the respective states.
Approach: They propose a large-scale dataset linking state bills and legislator information, geographical information about their districts, and donations and donors’ information.
Outcome: The proposed model improves over strong text-based models by integrating the state-level text and the legislative context.
Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts (2022.acl-long)

Copied to clipboard

Challenge: State-level legislation is the cornerstone of national policies and has long-lasting effects on residents of US states.
Approach: They build a dataset for multiple US states that interconnects multiple sources of data including bills, stakeholders, legislators, and money donors.
Outcome: The proposed model predicts winners/losers of bills and then utilizes them to determine the legislative body’s vote breakdown according to demographic/ideological criteria, e.g., gender.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations