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Sarcastic or Not: Word Embeddings to Predict the Literal or Sarcastic Meaning of Words
Debanjan Ghosh
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Weiwei Guo
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Smaranda Muresan
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Paper Details:
Month: September
Year: 2015
Location: Lisbon, Portugal
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Are Word Embedding-based Features Useful for Sarcasm Detection?
Aditya Joshi
|
Vaibhav Tripathi
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Kevin Patel
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Pushpak Bhattacharyya
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Mark Carman
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Robust Gram Embeddings
Taygun Kekeç
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David M. J. Tax
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Disambiguating False-Alarm Hashtag Usages in Tweets for Irony Detection
Hen-Hsen Huang
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Chiao-Chen Chen
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Hsin-Hsi Chen
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KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection
Luise Dürlich
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The Role of Conversation Context for Sarcasm Detection in Online Interactions
Debanjan Ghosh
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Alexander Richard Fabbri
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Smaranda Muresan
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Detecting Sarcasm is Extremely Easy ;-)
Natalie Parde
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Rodney Nielsen
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https://github.com/debanjanghosh/sarcasm
https://radimrehurek.com/gensim/models/word2vec.html
http://www.ark.cs.cmu.edu/TweetNLP/
http://nlp.stanford.edu/projects/glove/
Field Of Study
Linguistic Trends
Distributional Semantics
Embeddings
Task
Word Sense Disambiguation
Semantic Similarity
Approach
Kernel Method
Language
English
Dataset
Twitter
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