Get out the vote: Determining support or opposition from Congressional floor-debate transcripts

@inproceedings{Thomas2006GetOT,
  title={Get out the vote: Determining support or opposition from Congressional floor-debate transcripts},
  author={Matt Thomas and Bo Pang and Lillian Lee},
  booktitle={EMNLP},
  year={2006}
}
We investigate whether one can determine from the transcripts of U.S. Congressional floor debates whether the speeches represent support of or opposition to proposed legislation. To address this problem, we exploit the fact that these speeches occur as part of a discussion; this allows us to use sources of information regarding relationships between discourse segments, such as whether a given utterance indicates agreement with the opinion expressed by another. We find that the incorporation of… Expand

Tables and Topics from this paper

Analysis of speech transcripts to predict winners of U.S. Presidential and Vice-Presidential debates
TLDR
Investigations into the speech used in American Presidential and Vice-Presidential debates are described and a set of surface-level features from historical debates are found to predict the winners of presidential debates with success moderately above chance. Expand
Stance Classification using Dialogic Properties of Persuasion
TLDR
It is shown that representing the dialogic structure of the debates in terms of agreement relations between speakers, greatly improves performance for stance classification, over models that operate on post content and parent-post context alone. Expand
Computational Identification of Ideology in Text : A Study of Canadian Parliamentary Debates
In this study, we explore the task of classifying members of the 36th Canadian Parliament by ideology, which we approximate using party membership. Earlier work has been done on data from the U.S.Expand
Recognizing Disagreement in Informal Political Argument
The recent proliferation of political and social forums has given rise to a wealth of freely accessible naturalistic arguments. People can “talk” to anyone they want, at any time, in any location,Expand
Political Speech Generation
TLDR
A system that can generate political speeches for a desired political party using a combination of several state-of-the-art NLP methods, which has shown very high quality in terms of grammatical correctness and sentence transitions. Expand
Recognizing Stances in Ideological On-Line Debates
TLDR
This work constructs an arguing lexicon automatically from a manually annotated corpus and builds supervised systems employing sentiment and arguing opinions and their targets as features, which perform substantially better than a distribution-based baseline. Expand
Elements of a computational model for multi-party discourse: The turn-taking behavior of Supreme Court justices
TLDR
This paper explores computational models of multi-party discourse, using transcripts from U.S. Supreme Court oral arguments, and explores the hypothesis that discourse markers and personal references provide important features in such models. Expand
A Sentiment-labelled Corpus of Hansard Parliamentary Debate Speeches
Hansard transcripts provide access to Members of Parliament’s opinions on many important issues, but are difficult for people to process. Existing corpora for sentiment analysis in Hansard debatesExpand
Elements of a computational model for multi-party discourse: The turn-taking behavior of Supreme Court justices
TLDR
This work explores computational models of multi-party discourse, using transcripts from U.S. Supreme Court oral arguments, to explore the hypothesis that discourse markers and personal references provide important features in such models. Expand
How can you say such things?!?: Recognizing Disagreement in Informal Political Argument
The recent proliferation of political and social forums has given rise to a wealth of freely accessible naturalistic arguments. People can "talk" to anyone they want, at any time, in any location,Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 88 REFERENCES
Identifying Agreement and Disagreement in Conversational Speech: Use of Bayesian Networks to Model Pragmatic Dependencies
We describe a statistical approach for modeling agreements and disagreements in conversational interaction. Our approach first identifies adjacency pairs using maximum entropy ranking based on a setExpand
Detection Of Agreement vs. Disagreement In Meetings: Training With Unlabeled Data
TLDR
This work introduces a classifier to recognize agreement or disagreement utterances, utilizing both word-based and prosodic cues, and shows that hand-labeling efforts can be minimized by using unsupervisedTraining on a large unlabeled data set combined with supervised training on a small amount of data. Expand
A Preliminary Investigation into Sentiment Analysis of Informal Political Discourse
TLDR
Preliminary statistical tests on a new dataset of political discussion group postings indicate that posts made in direct response to other posts in a thread have a strong tendency to represent an opposing political viewpoint to the original post. Expand
Extracting Policy Positions from Political Texts Using Words as Data
We present a new way of extracting policy positions from political texts that treats texts not as discourses to be understood and interpreted but rather, as data in the form of words. We compare thisExpand
Summarizing Scientific Articles: Experiments with Relevance and Rhetorical Status
TLDR
This article provides a gold standard for summaries of this kind consisting of a substantial corpus of conference articles in computational linguistics annotated with human judgments of the rhetorical status and relevance of each sentence in the articles. Expand
Multidimensional text analysis for eRulemaking
TLDR
Techniques to automatically analyze large number of public comments on proposed regulations, performed on comments submitted to the Environmental Protection Agency in response to their proposed rule for mercury regulation, are developed. Expand
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
TLDR
A novel machine-learning method is proposed that applies text-categorization techniques to just the subjective portions of the document, which greatly facilitates incorporation of cross-sentence contextual constraints. Expand
Cultural Orientation: Classifying Subjective Documents by Cociation Analysis
  • M. Efron
  • Computer Science
  • AAAI Technical Report
  • 2004
TLDR
A simple method for estimating cultural orientation, the affiliation of hypertext documents in a polarized field of discourse, using a probabilistic model based on cocitation information is introduced. Expand
Automated classification of congressional legislation
TLDR
This paper presents the Congressional Bills Project's automated classification system and demonstrates that the automated system is about as effective as human assessors, but with significant time and cost savings. Expand
The American Congress
1. The American Congress: modern trends 2. Representation and lawmaking in Congress: the constitutional and historical context 3. Congressional elections and policy alignments 4. Members, goals,Expand
...
1
2
3
4
5
...