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TweeNLP
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On Using Twitter to Monitor Political Sentiment and Predict Election Results
Adam Bermingham
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Alan Smeaton
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Paper Details:
Month: November
Year: 2011
Location: Chiang Mai, Thailand
Venue:
WS |
Citations
URL
“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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Tweeting and Being Ironic in the Debate about a Political Reform: the French Annotated Corpus TWitter-MariagePourTous
Cristina Bosco
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Mirko Lai
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Viviana Patti
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Daniela Virone
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The First 100 Days: A Corpus Of Political Agendas on Twitter
Nathan Green
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Septina Larasati
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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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Classification of Moral Foundations in Microblog Political Discourse
Kristen Johnson
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Dan Goldwasser
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Identifying Stance by Analyzing Political Discourse on Twitter
Kristen Johnson
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Dan Goldwasser
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Using Author Embeddings to Improve Tweet Stance Classification
Adrian Benton
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Mark Dredze
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Measuring Issue Ownership using Word Embeddings
Amaru Cuba Gyllensten
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Magnus Sahlgren
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http://www.thejournal.ie
http://www.cs.waikato.ac.nz/ml/weka/
Field Of Study
Task
Sentiment Analysis
Language
English
Dataset
News
Social Media
Twitter
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