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Computational models for sarcasm detection have often relied on the content of utterances in isolation.
Syntax and semantics
H Paul Grice, Peter Cole, and Jerry L Morgan. 1975 · 1975
Earlier work this paper cites.
A speech act analysis of irony
Henk Haverkate. 1990 · 1990
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Irony markers and functions: Towards a goal-oriented theory of irony and its processing
Salvatore Attardo. 2000 · 2000
Earlier work this paper cites.
Linguistic inquiry and word count: Liwc 2001
James W Pennebaker, Martha E Francis, and Roger J Booth. 2001 · 2001
Earlier work this paper cites.
Mining and summarizing customer reviews
Minqing Hu and Bing Liu. 2004 · 2004
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.
Natural language processing with Python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper. 2009 · 2009
Earlier work this paper cites.
Semi-supervised recognition of sarcastic sentences in twitter and amazon
Dmitry Davidov, Oren Tsur, and Ari Rappoport. 2010 · 2010
Earlier work this paper cites.
LIBSVM: A library for support vector machines
Chih-Chung Chang and Chih-Jen Lin. 2011 · 2011
Earlier work this paper cites.
Part-of-speech tagging for twitter: Annotation, features, and experiments
Kevin Gimpel, Nathan Schneider, Brendan O’Connor, Dipanjan Das, Daniel Mills, Jacob Eisenstein, Michael Heilman, Dani Yogatama, Jeffrey Flanigan, and Noah A Smith. 2011 · 2011
Earlier work this paper cites.
Identifying sarcasm in twitter: A closer look
Roberto González-Ibáñez, Smaranda Muresan, and Nina Wacholder. 2011 · 2011
Earlier work this paper cites.
Verbal irony differences in usage across written genres
Christian Burgers, Margot Van Mulken, and Peter Jan Schellens. 2012 · 2012
Earlier work this paper cites.
Sarcasm, pretense, and the semantics/pragmatics distinction*
Elisabeth Camp. 2012 · 2012
Cited alongside, same era.
The perfect solution for detecting sarcasm in tweets# not
CC Liebrecht, FA Kunneman, and APJ van den Bosch. 2013 · 2013
Cited alongside, same era.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Cited alongside, same era.
Sarcasm as contrast between a positive sentiment and negative situation
Ellen Riloff, Ashequl Qadir, Prafulla Surve, Lalindra De Silva, Nathan Gilbert, and Ruihong Huang. 2013 · 2013
Cited alongside, same era.
Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis
Diana Maynard and Mark A Greenwood. 2014 · 2014
Cited alongside, same era.
Your sentiment precedes you: Using an author’s historical tweets to predict sarcasm
Anupam Khattri, Aditya Joshi, Pushpak Bhattacharyya, and Mark James Carman. 2015 · 2015
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Sarcasm detection on twitter: A behavioral modeling approach
Ashwin Rajadesingan, Reza Zafarani, and Huan Liu. 2015 · 2015
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Reasoning about entailment with neural attention
Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomáš Kočiskỳ, and Phil Blunsom. 2015 · 2015
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Grammar as a foreign language
Oriol Vinyals, Łukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, and Geoffrey Hinton. 2015 · 2015
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Twitter sarcasm detection exploiting a context-based model
Zelin Wang, Zhijian Wu, Ruimin Wang, and Yafeng Ren. 2015 · 2015
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Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Cited alongside, same era.
Emoticons and phrases: Status symbols in social media
Simo Tchokni, Diarmuid O Séaghdha, and Daniele Quercia. 2014 · 2014
Cited alongside, same era.
Humans require context to infer ironic intent (so computers probably do, too)
Byron C Wallace, Laura Kertz Do Kook Choe, Laura Kertz, and Eugene Charniak. 2014 · 2014
Cited alongside, same era.
Recurrent neural network regularization
Wojciech Zaremba, Ilya Sutskever, and Oriol Vinyals. 2014 · 2014
Cited alongside, same era.
Contextualized sarcasm detection on twitter
David Bamman and Noah A Smith. 2015 · 2015
Cited alongside, same era.
A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning. 2015 · 2015
Cited alongside, same era.
Sarcastic or not: Word embeddings to predict the literal or sarcastic meaning of words
Debanjan Ghosh, Weiwei Guo, and Smaranda Muresan. 2015 · 2015
Cited alongside, same era.
Wenpeng Yin, Hinrich Schütze, Bing Xiang, and Bowen Zhou. 2015 · 2015
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Fracking sarcasm using neural network
Aniruddha Ghosh and Tony Veale. 2016 · 2016
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Are word embedding-based features useful for sarcasm detection?
Aditya Joshi, Vaibhav Tripathi, Kevin Patel, Pushpak Bhattacharyya, and Mark Carman. 2016 · 2016
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Identification of nonliteral language in social media: A case study on sarcasm
Smaranda Muresan, Roberto Gonzalez-Ibanez, Debanjan Ghosh, and Nina Wacholder. 2016 · 2016
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Creating and characterizing a diverse corpus of sarcasm in dialogue
Shereen Oraby, Vrindavan Harrison, Ernesto Hernandez, Lena Reed, Ellen Riloff, and Marilyn Walker. 2016 · 2016
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A decomposable attention model for natural language inference
Ankur P Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. 2016 · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio. 2015 · 2057
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