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The 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance classification task as a crucial first step towards detecting fake news.
The argument reasoning comprehension task: Identification and reconstruction of implicit warrants
Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, and Benno Stein. 2018 · 1940
Earlier work this paper cites.
Automated readability index
R.J. Senter and Edgar A. Smith. 1967 · 1967
Earlier work this paper cites.
SMOG grading—a new readability formula
G. Harry Mc Laughlin. 1969 · 1969
Earlier work this paper cites.
Measuring nominal scale agreement among many raters
Joseph L. Fleiss. 1971 · 1971
Earlier work this paper cites.
Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel
J. Peter Kincaid, Robert P. Fishburne Jr, Richard L. Rogers, and Brad S. Chissom. 1975 · 1975
Earlier work this paper cites.
A computer readability formula designed for machine scoring
Coleman Mari and Liau Ta Lin. 1975 · 1975
Earlier work this paper cites.
Lix and Rix: Variations on a Little-known Readability Index
Anderson Jonathan. 1983 · 1983
Earlier work this paper cites.
Indexing by latent semantic analysis
Scott Deerwester, Susan T Dumais, George W Furnas, Thomas K Landauer, and Richard Harshman. 1990 · 1990
Earlier work this paper cites.
Global English for global business
Rachel McAlpine. 1997 · 1997
Earlier work this paper cites.
Latent dirichlet allocation
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2001 · 2001
Earlier work this paper cites.
An assessment of the range and usefulness of lexical diversity measures and the potential of the measure of textual, lexical diversity (MTLD)
Philip M. McCarthy. 2005 · 2005
Earlier work this paper cites.
Recognizing contextual polarity in phrase-level sentiment analysis
Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005 · 2005
Earlier work this paper cites.
Strain Index: A New Readability Formula
N. Watson Solomon. 2006 · 2006
Earlier work this paper cites.
Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
Sanjiv R. Das and Mike Y. Chen. 2007 · 2007
Earlier work this paper cites.
Projected gradient methods for nonnegative matrix factorization
Chih-Jen Lin. 2007 · 2007
Earlier work this paper cites.
Inter-coder agreement for computational linguistics
Ron Artstein and Massimo Poesio. 2008 · 2008
Earlier work this paper cites.
Emotions Evoked by Common Words and Phrases: Using Mechanical Turk to Create an Emotion Lexicon
Saif M. Mohammad and Peter D. Turney. 2010 · 2010
Earlier work this paper cites.
Recognizing stances in ideological on-line debates
Swapna Somasundaran and Janyce Wiebe. 2010 · 2010
Cited alongside, same era.
What can readability measures really tell us about text complexity
Sanja Štajner, Richard Evans, Constantin Orăsan, and Ruslan Mitkov. 2012 · 2012
Cited alongside, same era.
Stance classification using dialogic properties of persuasion
Marilyn A. Walker, Pranav Anand, Robert Abbott, and Ricky Grant. 2012 · 2012
Cited alongside, same era.
Stance Classification of Ideological Debates: Data, Models, Features, and Constraints
Kazi Saidul Hasan and Vincent Ng. 2013 · 2013
Cited alongside, same era.
Training and analysing deep recurrent neural networks
Michiel Hermans and Benjamin Schrauwen. 2013 · 2013
Cited alongside, same era.
Learning Whom to Trust with MACE
Dirk Hovy, Taylor Berg-Kirkpatrick, Ashish Vaswani, and Eduard Hovy. 2013 · 2013
SemEval-2016 Task 6: Detecting Stance in Tweets
Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016 · 2016
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MITRE at SemEval-2016 Task 6: Transfer Learning for Stance Detection
Guido Zarrella and Amy Marsh. 2016 · 2016
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From Clickbait to Fake News Detection: An Approach based on Detecting the Stance of Headlines to Articles
Peter Bourgonje, Julian Moreno Schneider, and Georg Rehm. 2017 · 2017
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SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours
Leon Derczynski, Kalina Bontcheva, Maria Liakata, Rob Procter, Geraldine Wong Sak Hoi, and Arkaitz Zubiaga. 2017 · 2017
Later among the works it cites.
Stance classification with target-specific neural attention
Jiachen Du, Ruifeng Xu, Yulan He, and Lin Gui. 2017 · 2017
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Cited alongside, same era.
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets
Saif M. Mohammad, Svetlana Kiritchenko, and Xiaodan Zhu. 2013 · 2013
Cited alongside, same era.
Crowdsourcing a word-emotion association lexicon 29(3):436–465
Saif M. Mohammad and Peter D. Turney. 2013 · 2013
Cited alongside, same era.
Sentiment analysis of short informal texts
Svetlana Kiritchenko, Xiaodan Zhu, and Saif M. Mohammad. 2014 · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
Cited alongside, same era.
NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets
Xiaodan Zhu, Svetlana Kiritchenko, and Saif M. Mohammad. 2014 · 2014
Cited alongside, same era.
SemEval-2015 Task 10: Sentiment Analysis in Twitter
Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif Mohammad, Alan Ritter, and Veselin Stoyanov. 2015 · 2015
Cited alongside, same era.
This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News
Benjamin D. Horne and Sibel Adali. 2017 · 2017
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The Fake News Challenge: Exploring how artificial intelligence technologies could be leveraged to combat fake news
Dean Pomerleau and Delip Rao. 2017 · 2017
Later among the works it cites.
A simple but tough-to-beat baseline for the fake news challenge stance detection task
Benjamin Riedel, Isabelle Augenstein, Georgios P Spithourakis, and Sebastian Riedel. 2017 · 2017
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Talos Targets Disinformation with Fake News Challenge Victory
Baird Sean, Sibley Doug, and Pan Yuxi. 2017 · 2017
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Fake news detection on social media: A data mining perspective
Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. 2017 · 2017
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Emergent: A real-time rumor tracker
Craig Silverman. 2017 · 2017
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Parsing argumentation structures in persuasive essays
Christian Stab and Iryna Gurevych. 2017 · 2017
Later among the works it cites.
Overview of the Task on Stance and Gender Detection in Tweets on Catalan Independence
Mariona Taulé, Maria Antònia Martí, Francisco M. Rangel Pardo, Paolo Rosso, Cristina Bosco, and Viviana Patti. 2017 · 2017
Later among the works it cites.
Fake news stance detection using stacked ensemble of classifiers
James Thorne, Mingjie Chen, Giorgos Myrianthous, Jiashu Pu, Xiaoxuan Wang, and Andreas Vlachos. 2017 · 2017
Later among the works it cites.
Fake News, Real Consequences: Recruiting Neural Networks for the Fight Against Fake News
Richard Davis and Chris Proctor. 2017 · 2018
Closest in time.
Description of the system developed by team Athene in the FNC-1, 2017
Andreas Hanselowski, Avinesh PVS, Benjamin Schiller, and Felix Caspelherr. 2017 · 2018
Closest in time.