UWB at SemEval-2016 Task 6: Stance Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43929366" target="_blank" >RIV/49777513:23520/16:43929366 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
UWB at SemEval-2016 Task 6: Stance Detection
Original language description
This paper describes our system participating in the SemEval 2016 task: Detecting stance in Tweets. The goal was to identify whether the author of a tweet is in favor of the given target or against. Our approach is based on a maximum entropy classifier, which uses surface-level, sentiment and domain-specific features. We participated in both the supervised and weakly supervised subtasks and received promising results for most of the targets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The 10th InternationalWorkshop on Semantic Evaluation
ISBN
978-1-941643-95-2
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
408-412
Publisher name
Association for Computational Linguistics (ACL)
Place of publication
Stroudsburg
Event location
San Diego, CA
Event date
Jun 16, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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