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Recent work in automated sarcasm detection has placed a heavy focus on context and meta-data.
"yeah right": Sarcasm recognition for spoken dialogue systems
Joseph Tepperman, David R. Traum, and Shrikanth Narayanan · 2006
Earlier work this paper cites.
Opinion mining and sentiment analysis
Bo Pang and Lillian Lee · 2007
Earlier work this paper cites.
A unified architecture for natural language processing: deep neural networks with multitask learning
Ronan Collobert and Jason Weston · 2008
Earlier work this paper cites.
Clues for detecting irony in user-generated contents: oh…!! it’s "so easy" ;-)
Paula Carvalho, Luís Sarmento, Mário J. Silva, and Eugénio de Oliveira · 2009
Earlier work this paper cites.
Semi-supervised recognition of sarcastic sentences in twitter and amazon
Dmitry Davidov, Oren Tsur, and Ari Rappoport · 2010
Earlier work this paper cites.
Identifying sarcasm in twitter: A closer look
Roberto I. González-Ibáñez, Smaranda Muresan, and Nina Wacholder · 2011
Earlier work this paper cites.
The perfect solution for detecting sarcasm in tweets #not
Christine Liebrecht, Florian Kunneman, and Antal van den Bosch · 2013
Earlier work this paper cites.
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
Earlier work this paper cites.
A multidimensional approach for detecting irony in twitter
Antonio Reyes, Paolo Rosso, and Tony Veale · 2013
Earlier work this paper cites.
An impact analysis of features in a classification approach to irony detection in product reviews
Konstantin Buschmeier, Philipp Cimiano, and Roman Klinger · 2014
Earlier work this paper cites.
Sarcasm detection on czech and english twitter
Tomás Ptácek, Ivan Habernal, and Jun Hong · 2014
Cited alongside, same era.
Humans require context to infer ironic intent (so computers probably do, too)
Byron C. Wallace, Do Kook Choe, Laura Kertz, and Eugene Charniak · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Contextualized sarcasm detection on twitter
David Bamman and Noah A. Smith · 2015
Cited alongside, same era.
Sparse, contextually informed models for irony detection: Exploiting user communities, entities and sentiment
Byron C. Wallace, Do Kook Choe, and Eugene Charniak · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Fracking sarcasm using neural network
Aniruddha Ghosh and Tony Veale · 2016
Later among the works it cites.
Densely connected convolutional networks
Gao Huang, Zhuang Liu, and Kilian Q. Weinberger · 2016
Later among the works it cites.
Very deep convolutional networks for text classification
Holger Schwenk, Loïc Barrault, Alexis Conneau, and Yann LeCun · 2016
Later among the works it cites.
Exploring the impact of pragmatic phenomena on irony detection in tweets: A multilingual corpus study
Jihen Karoui, Benamara Farah, Véronique Moriceau, Viviana Patti, Cristina Bosco, and Nathalie Aussenac-Gilles · 2017
Later among the works it cites.
Phonetic-based microtext normalization for twitter sentiment analysis
Ranjan Satapathy, Claudia Guerreiro, Iti Chaturvedi, and Erik Cambria · 2017
Later among the works it cites.
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
Cyclical learning rates for training neural networks
Leslie N. Smith · 2015
Cited alongside, same era.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
Modelling context with user embeddings for sarcasm detection in social media
Silvio Amir, Byron C. Wallace, Hao Lyu, Paula Carvalho, and Mário J. Silva · 2016
Cited alongside, same era.
A deeper look into sarcastic tweets using deep convolutional neural networks
Soujanya Poria, Erik Cambria, Devamanyu Hazarika, and Prateek Vij · 2016
Cited alongside, same era.
Mikhail Khodak, Nikunj Saunshi, and Kiran Vodrahalli · 2017
Later among the works it cites.
Attentional multi-reading sarcasm detection
Reza Ghaeini, Xiaoli Z. Fern, and Prasad Tadepalli · 2018
Later among the works it cites.
Cascade: Contextual sarcasm detection in online discussion forums
Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, Erik Cambria, Roger Zimmermann, and Rada Mihalcea · 2018
Later among the works it cites.
Advances in pre-training distributed word representations
Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin · 2018
Later among the works it cites.