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Open Extraction of Fine-Grained Political Statements
David Bamman
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Noah A. Smith
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Paper Details:
Month: September
Year: 2015
Location: Lisbon, Portugal
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Anecdote Recognition and Recommendation
Wei Song
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Ruiji Fu
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Lizhen Liu
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Hanshi Wang
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Ting Liu
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“All I know about politics is what I read in Twitter”: Weakly Supervised Models for Extracting Politicians’ Stances From Twitter
Kristen Johnson
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Dan Goldwasser
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Crowdsourcing a Large Dataset of Domain-Specific Context-Sensitive Semantic Verb Relations
Maria Sukhareva
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Judith Eckle-Kohler
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Ivan Habernal
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Iryna Gurevych
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Leveraging Behavioral and Social Information for Weakly Supervised Collective Classification of Political Discourse on Twitter
Kristen Johnson
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Di Jin
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Dan Goldwasser
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Efficient Online Scalar Annotation with Bounded Support
Keisuke Sakaguchi
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Benjamin Van Durme
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Classification of Moral Foundations in Microblog Political Discourse
Kristen Johnson
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Dan Goldwasser
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Towards a text analysis system for political debates
Dieu-Thu Le
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Ngoc Thang Vu
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Andre Blessing
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Identifying Stance by Analyzing Political Discourse on Twitter
Kristen Johnson
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Dan Goldwasser
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Dave the debater: a retrieval-based and generative argumentative dialogue agent
Dieu Thu Le
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Cam-Tu Nguyen
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Kim Anh Nguyen
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http://www.npr.org
http://www.motherjones.com
http://www.politico.com
http://www.breitbart.com
http://dailycaller.com
http://www.youngcons.com
https://www.ijreview.com
https://disqus.com/api/
http://people.ischool
http://research.microsoft
http://blogs.law.harvard
Field Of Study
Linguistic Trends
Ontologies
Task
Information Extraction
Language
English
Dataset
News
Social Media
Twitter
Blogs
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