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Stance Detection with Bidirectional Conditional Encoding
Isabelle Augenstein
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Tim Rocktäschel
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Andreas Vlachos
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Kalina Bontcheva
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Paper Details:
Month: November
Year: 2016
Location: Austin, Texas
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets
Javid Ebrahimi
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Dejing Dou
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Daniel Lowd
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CNN- and LSTM-based Claim Classification in Online User Comments
Chinnappa Guggilla
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Tristan Miller
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Iryna Gurevych
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A Retrospective Analysis of the Fake News Challenge Stance-Detection Task
Andreas Hanselowski
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Avinesh PVS
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Benjamin Schiller
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Felix Caspelherr
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Debanjan Chaudhuri
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Christian M. Meyer
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Iryna Gurevych
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Stance Detection with Hierarchical Attention Network
Qingying Sun
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Zhongqing Wang
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Qiaoming Zhu
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Guodong Zhou
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Structured Representation Learning for Online Debate Stance Prediction
Chang Li
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Aldo Porco
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Dan Goldwasser
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A strong baseline for question relevancy ranking
Ana Gonzalez
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Isabelle Augenstein
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Anders Søgaard
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Sentiment-Stance-Specificity (SSS) Dataset: Identifying Support-based Entailment among Opinions.
Pavithra Rajendran
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Danushka Bollegala
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Simon Parsons
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Multi-Task Learning of Pairwise Sequence Classification Tasks over Disparate Label Spaces
Isabelle Augenstein
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Sebastian Ruder
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Anders Søgaard
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Cross-Target Stance Classification with Self-Attention Networks
Chang Xu
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Cécile Paris
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Surya Nepal
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Ross Sparks
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Simple Open Stance Classification for Rumour Analysis
Ahmet Aker
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Leon Derczynski
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Kalina Bontcheva
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Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM
Elena Kochkina
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Maria Liakata
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Isabelle Augenstein
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Constructive Language in News Comments
Varada Kolhatkar
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Maite Taboada
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From Clickbait to Fake News Detection: An Approach based on Detecting the Stance of Headlines to Articles
Peter Bourgonje
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Julian Moreno Schneider
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Georg Rehm
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Using New York Times Picks to Identify Constructive Comments
Varada Kolhatkar
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Maite Taboada
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Automatic detection of stance towards vaccination in online discussion forums
Maria Skeppstedt
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Andreas Kerren
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Manfred Stede
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Using Author Embeddings to Improve Tweet Stance Classification
Adrian Benton
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Mark Dredze
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https://dev.twitter.com/rest/public/
https://github.com/leondz/twokenize
https://github.com/
http://www.pheme.eu
Field Of Study
Linguistic Trends
Embeddings
Task
Textual Entailment
Sentiment Analysis
Language
English
Dataset
Social Media
Twitter
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