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Detecting Stance in Tweets And Analyzing its Interaction with Sentiment
Parinaz Sobhani
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Saif Mohammad
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Svetlana Kiritchenko
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Paper Details:
Month: August
Year: 2016
Location: Berlin, Germany
Venue:
*SEMEVAL |
Citations
URL
A Dataset for Multi-Target Stance Detection
Parinaz Sobhani
|
Diana Inkpen
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Xiaodan Zhu
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EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis
Sven Buechel
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Udo Hahn
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Representation Mapping: A Novel Approach to Generate High-Quality Multi-Lingual Emotion Lexicons
Sven Buechel
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Udo Hahn
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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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Toward Stance Classification Based on Claim Microstructures
Filip Boltužić
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Jan Šnajder
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http://alt.qcri.org/semeval2016/task6/
http://alt.qcri.org/semeval2016/task6/
http://www.crowdflower.com
Field Of Study
Linguistic Trends
Embeddings
Task
Tagging
Named Entity Recognition
Sentiment Analysis
Argumentation Mining
Text Categorization
Language
English
Dataset
News
Twitter
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