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Sarcasm as Contrast between a Positive Sentiment and Negative Situation
Ellen Riloff
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Ashequl Qadir
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Prafulla Surve
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Lalindra De Silva
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Nathan Gilbert
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Ruihong Huang
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Paper Details:
Month: October
Year: 2013
Location: Seattle, Washington, USA
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Sarcasm Detection on Czech and English Twitter
Tomáš Ptáček
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Ivan Habernal
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Jun Hong
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A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks
Soujanya Poria
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Erik Cambria
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Devamanyu Hazarika
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Prateek Vij
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Tweet Sarcasm Detection Using Deep Neural Network
Meishan Zhang
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Yue Zhang
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Guohong Fu
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Monday mornings are my fave :) #not Exploring the Automatic Recognition of Irony in English tweets
Cynthia Van Hee
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Els Lefever
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Véronique Hoste
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CASCADE: Contextual Sarcasm Detection in Online Discussion Forums
Devamanyu Hazarika
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Soujanya Poria
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Sruthi Gorantla
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Erik Cambria
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Roger Zimmermann
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Rada Mihalcea
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Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for German
Marc Schulder
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Michael Wiegand
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Josef Ruppenhofer
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+/-EffectWordNet: Sense-level Lexicon Acquisition for Opinion Inference
Yoonjung Choi
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Janyce Wiebe
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Learning Emotion Indicators from Tweets: Hashtags, Hashtag Patterns, and Phrases
Ashequl Qadir
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Ellen Riloff
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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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Are Word Embedding-based Features Useful for Sarcasm Detection?
Aditya Joshi
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Vaibhav Tripathi
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Kevin Patel
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Pushpak Bhattacharyya
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Mark Carman
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Attentive Gated Lexicon Reader with Contrastive Contextual Co-Attention for Sentiment Classification
Yi Tay
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Anh Tuan Luu
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Siu Cheung Hui
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Jian Su
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Sentiment Propagation via Implicature Constraints
Lingjia Deng
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Janyce Wiebe
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Leveraging Cognitive Features for Sentiment Analysis
Abhijit Mishra
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Diptesh Kanojia
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Seema Nagar
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Kuntal Dey
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Pushpak Bhattacharyya
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Modelling Context with User Embeddings for Sarcasm Detection in Social Media
Silvio Amir
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Byron C. Wallace
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Hao Lyu
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Paula Carvalho
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Mário J. Silva
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Getting Reliable Annotations for Sarcasm in Online Dialogues
Reid Swanson
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Stephanie Lukin
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Luke Eisenberg
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Thomas Corcoran
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Marilyn Walker
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Deep Learning of Audio and Language Features for Humor Prediction
Dario Bertero
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Pascale Fung
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Exploring the Realization of Irony in Twitter Data
Cynthia Van Hee
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Els Lefever
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Véronique Hoste
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A Large Self-Annotated Corpus for Sarcasm
Mikhail Khodak
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Nikunj Saunshi
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Kiran Vodrahalli
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An Integrated Representation of Linguistic and Social Functions of Code-Switching
Silvana Hartmann
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Monojit Choudhury
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Kalika Bali
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A Long Short-Term Memory Framework for Predicting Humor in Dialogues
Dario Bertero
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Pascale Fung
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The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter
Chenhao Tan
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Lillian Lee
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Bo Pang
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Measuring Sentiment Annotation Complexity of Text
Aditya Joshi
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Abhijit Mishra
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Nivvedan Senthamilselvan
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Pushpak Bhattacharyya
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Humans Require Context to Infer Ironic Intent (so Computers Probably do, too)
Byron C. Wallace
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Do Kook Choe
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Laura Kertz
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Eugene Charniak
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Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment
Byron C. Wallace
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Do Kook Choe
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Eugene Charniak
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Towards a Contextual Pragmatic Model to Detect Irony in Tweets
Jihen Karoui
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Farah Benamara Zitoune
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Véronique Moriceau
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Nathalie Aussenac-Gilles
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Lamia Hadrich Belguith
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Harnessing Context Incongruity for Sarcasm Detection
Aditya Joshi
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Vinita Sharma
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Pushpak Bhattacharyya
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Harnessing Cognitive Features for Sarcasm Detection
Abhijit Mishra
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Diptesh Kanojia
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Seema Nagar
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Kuntal Dey
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Pushpak Bhattacharyya
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Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network
Abhijit Mishra
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Kuntal Dey
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Pushpak Bhattacharyya
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Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation
Lotem Peled
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Roi Reichart
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Reasoning with Sarcasm by Reading In-Between
Yi Tay
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Anh Tuan Luu
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Siu Cheung Hui
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Jian Su
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Understanding Satirical Articles Using Common-Sense
Dan Goldwasser
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Xiao Zhang
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Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science
Emily M. Bender
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Batya Friedman
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LLT-PolyU: Identifying Sentiment Intensity in Ironic Tweets
Hongzhi Xu
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Enrico Santus
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Anna Laszlo
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Chu-Ren Huang
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ValenTo: Sentiment Analysis of Figurative Language Tweets with Irony and Sarcasm
Delia Irazú Hernández Farías
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Emilio Sulis
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Viviana Patti
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Giancarlo Ruffo
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Cristina Bosco
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NLDS-UCSC at SemEval-2016 Task 6: A Semi-Supervised Approach to Detecting Stance in Tweets
Amita Misra
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Brian Ecker
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Theodore Handleman
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Nicolas Hahn
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Marilyn Walker
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CrystalNest at SemEval-2017 Task 4: Using Sarcasm Detection for Enhancing Sentiment Classification and Quantification
Raj Kumar Gupta
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Yinping Yang
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SemEval-2018 Task 3: Irony Detection in English Tweets
Cynthia Van Hee
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Els Lefever
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Véronique Hoste
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WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony
Omid Rohanian
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Shiva Taslimipoor
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Richard Evans
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Ruslan Mitkov
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Random Decision Syntax Trees at SemEval-2018 Task 3: LSTMs and Sentiment Scores for Irony Detection
Aidan San
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IronyMagnet at SemEval-2018 Task 3: A Siamese network for Irony detection in Social media
Aniruddha Ghosh
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Tony Veale
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INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter
Delia Irazú Hernández Farías
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Fernando Sánchez-Vega
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Manuel Montes-y-Gómez
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Paolo Rosso
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Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection
Nishant Nikhil
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Muktabh Mayank Srivastava
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ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets
Delia Irazú Hernández Farías
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Viviana Patti
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Paolo Rosso
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#NonDicevoSulSerio at SemEval-2018 Task 3: Exploiting Emojis and Affective Content for Irony Detection in English Tweets
Endang Wahyu Pamungkas
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Viviana Patti
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How Challenging is Sarcasm versus Irony Classification?: A Study With a Dataset from English Literature
Aditya Joshi
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Vaibhav Tripathi
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Pushpak Bhattacharyya
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Mark Carman
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Meghna Singh
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Jaya Saraswati
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Rajita Shukla
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Modelling Sarcasm in Twitter, a Novel Approach
Francesco Barbieri
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Horacio Saggion
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Francesco Ronzano
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Lexical Acquisition for Opinion Inference: A Sense-Level Lexicon of Benefactive and Malefactive Events
Yoonjung Choi
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Lingjia Deng
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Janyce Wiebe
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Your Sentiment Precedes You: Using an author’s historical tweets to predict sarcasm
Anupam Khattri
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Aditya Joshi
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Pushpak Bhattacharyya
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Mark Carman
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Fracking Sarcasm using Neural Network
Aniruddha Ghosh
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Tony Veale
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How Do Cultural Differences Impact the Quality of Sarcasm Annotation?: A Case Study of Indian Annotators and American Text
Aditya Joshi
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Pushpak Bhattacharyya
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Mark Carman
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Jaya Saraswati
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Rajita Shukla
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Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue
Shereen Oraby
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Vrindavan Harrison
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Lena Reed
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Ernesto Hernandez
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Ellen Riloff
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Marilyn Walker
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Automatic Recognition of Conversational Strategies in the Service of a Socially-Aware Dialog System
Ran Zhao
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Tanmay Sinha
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Alan Black
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Justine Cassell
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Sarcasm Detection : Building a Contextual Hierarchy
Taradheesh Bali
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Navjyoti Singh
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‘Who would have thought of that!’: A Hierarchical Topic Model for Extraction of Sarcasm-prevalent Topics and Sarcasm Detection
Aditya Joshi
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Prayas Jain
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Pushpak Bhattacharyya
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Mark Carman
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A Survey on Hate Speech Detection using Natural Language Processing
Anna Schmidt
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Michael Wiegand
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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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Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog
Shereen Oraby
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Vrindavan Harrison
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Amita Misra
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Ellen Riloff
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Marilyn Walker
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Detecting Sarcasm is Extremely Easy ;-)
Natalie Parde
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Rodney Nielsen
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Deep contextualized word representations for detecting sarcasm and irony
Suzana Ilić
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Edison Marrese-Taylor
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Jorge Balazs
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Yutaka Matsuo
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http://en.wikipedia.org/wiki/List
http://arxiv.org/abs/1103.2903
Field Of Study
Approach
Semi-supervised Learning
Language
English
Dataset
Twitter
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