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ltl.uni-due at SemEval-2016 Task 6: Stance Detection in Social Media Using Stacked Classifiers

In this paper, we describe our participation in the first shared task on automated stance detection (SemEval 2016 Task 6). We consider the task as a multidimensional classification problem and thus use a sequence of stacked classifiers. For subtask A, we utilize a rich feature set that does not rely on external information such as additional tweets or knowledge bases. For subtask B, we rely on the similarity of tweets in this task with tweets from subtask A in order to transfer the models learnt in subtask A.

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Conference:
10th International Workshop on Semantic Evaluation (SemEval-2016), June 16-17, 2016 San Diego, California, USA
Date Issued:
2016
URN:
urn:nbn:de:hbz:464-20180704-101227-1
DOI:
10.18653/v1/S16-1069
Language:
English
Type of Resource:
Text
Collection:
E-Publications
Dewey Decimal Classification:
000 Computer science, knowledge & systems
Subject categories of the Deutsche Nationalbibliografie:
000 Generalities, Science
URL:
http://www.aclweb.org/anthology/S16-1069
Hosting institution:
Faculty of Engineering, Computer Science and Applied Cognitive Science
Hosting institution:
Scientific institutes, Institute for optional studies (IOS)
Info on primary publication:
Proceedings of SemEval-2016, pages 428–433, San Diego, California, June 16-17, 2016 (ISBN 978-1-941643-95-2). DOI: https://doi.org/10.18653/v1/S16-1069

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