Sarcasm Detection with Self-matching Networks and Low-rank Bilinear Pooling
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Hongbo Zhu | Tao Xiong | Peiran Zhang | Yihui Yang | T. Xiong | Hongbo Zhu | Peiran Zhang | Yihui Yang
[1] Tony Veale,et al. Fracking Sarcasm using Neural Network , 2016, WASSA@NAACL-HLT.
[2] A. Katz,et al. Are There Necessary Conditions for Inducing a Sense of Sarcastic Irony? , 2012 .
[3] Pushpak Bhattacharyya,et al. Are Word Embedding-based Features Useful for Sarcasm Detection? , 2016, EMNLP.
[4] Ari Rappoport,et al. Semi-Supervised Recognition of Sarcasm in Twitter and Amazon , 2010, CoNLL.
[5] Pushpak Bhattacharyya,et al. Automatic Sarcasm Detection: A Survey , 2016 .
[6] Jun Hong,et al. Sarcasm Detection on Czech and English Twitter , 2014, COLING.
[7] Diana Maynard,et al. Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis. , 2014, LREC.
[8] Byron C. Wallace,et al. Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment , 2015, ACL.
[9] Pushpak Bhattacharyya,et al. Harnessing Context Incongruity for Sarcasm Detection , 2015, ACL.
[10] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[11] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[12] Pushpak Bhattacharyya,et al. Harnessing Sequence Labeling for Sarcasm Detection in Dialogue from TV Series ‘Friends’ , 2016, CoNLL.
[13] Jiasen Lu,et al. Hierarchical Question-Image Co-Attention for Visual Question Answering , 2016, NIPS.
[14] Marilyn A. Walker,et al. Really? Well. Apparently Bootstrapping Improves the Performance of Sarcasm and Nastiness Classifiers for Online Dialogue , 2013, ArXiv.
[15] Penny M. Pexman,et al. Context Incongruity and Irony Processing , 2003 .
[16] Ellen Riloff,et al. Sarcasm as Contrast between a Positive Sentiment and Negative Situation , 2013, EMNLP.
[17] RossoPaolo,et al. A multidimensional approach for detecting irony in Twitter , 2013 .
[18] Paolo Rosso,et al. Making objective decisions from subjective data: Detecting irony in customer reviews , 2012, Decis. Support Syst..
[19] Nathalie Aussenac-Gilles,et al. Towards a Contextual Pragmatic Model to Detect Irony in Tweets , 2015, ACL.
[20] Diyi Yang,et al. Hierarchical Attention Networks for Document Classification , 2016, NAACL.
[21] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[22] Marilyn A. Walker,et al. A Corpus for Research on Deliberation and Debate , 2012, LREC.
[23] Yue Zhang,et al. Tweet Sarcasm Detection Using Deep Neural Network , 2016, COLING.
[24] Reza Zafarani,et al. Sarcasm Detection on Twitter: A Behavioral Modeling Approach , 2015, WSDM.
[25] Tony Veale,et al. Detecting Ironic Intent in Creative Comparisons , 2010, ECAI.
[26] Sanjay Kumar Jena,et al. Parsing-based sarcasm sentiment recognition in Twitter data , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[27] Tony Veale,et al. Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal , 2017, EMNLP.
[28] Byron C. Wallace,et al. Modelling Context with User Embeddings for Sarcasm Detection in Social Media , 2016, CoNLL.
[29] Ari Rappoport,et al. ICWSM - A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews , 2010, ICWSM.
[30] Nina Wacholder,et al. Identifying Sarcasm in Twitter: A Closer Look , 2011, ACL.
[31] Elisabeth Camp. Sarcasm, Pretense, and The Semantics/ Pragmatics Distinction ∗ , 2012 .
[32] Antal van den Bosch,et al. The perfect solution for detecting sarcasm in tweets #not , 2013, WASSA@NAACL-HLT.
[33] Paolo Rosso,et al. A multidimensional approach for detecting irony in Twitter , 2013, Lang. Resour. Evaluation.
[34] Jian Su,et al. Reasoning with Sarcasm by Reading In-Between , 2018, ACL.
[35] Tomoaki Ohtsuki,et al. Opinion mining in Twitter: How to make use of sarcasm to enhance sentiment analysis , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[36] Navneet Kaur,et al. Opinion mining and sentiment analysis , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).
[37] Davide Buscaldi,et al. From humor recognition to irony detection: The figurative language of social media , 2012, Data Knowl. Eng..
[38] Horacio Saggion,et al. Modelling Sarcasm in Twitter, a Novel Approach , 2014, WASSA@ACL.