2022
DOI: 10.1086/714928
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Bill Text and Agenda Control in the US Congress

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Cited by 4 publications
(2 citation statements)
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“…Any word, phrase, or document can be represented as a vector of real numbers (Mikolov et al 2013; Pennington, Socher, and Manning 2014) by assuming it is possible to know the meaning of a word by the words that typically surround it (Firth 1957). Embeddings enable a wide array of mathematical approaches that would be impossible with raw text alone or commonly employed topic models (e.g., Ballard 2022). However, neither dictionary methods nor fixed embedding is adaptable to context, as words are assigned a single fixed value (a sentiment score or numeric vector).…”
Section: Methodsmentioning
confidence: 99%
“…Any word, phrase, or document can be represented as a vector of real numbers (Mikolov et al 2013; Pennington, Socher, and Manning 2014) by assuming it is possible to know the meaning of a word by the words that typically surround it (Firth 1957). Embeddings enable a wide array of mathematical approaches that would be impossible with raw text alone or commonly employed topic models (e.g., Ballard 2022). However, neither dictionary methods nor fixed embedding is adaptable to context, as words are assigned a single fixed value (a sentiment score or numeric vector).…”
Section: Methodsmentioning
confidence: 99%
“…House minority parties shape the issue attentions of the majority party (Hughes 2018) as well as the floor roll-call record (Egar 2016). Majority parties are often unable to control the House floor agenda (Ballard and Curry 2020), and there are virtually no differences between the negative agenda-setting powers exercised by House and Senate majority parties, despite far more favorable rules in the House (Ballard 2021;Gailmard and Jenkins 2007;. Meaningful minority party influence is not a rare occurrence.…”
mentioning
confidence: 99%