IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification

Yi-Chin Chen, Zhao-Yang Liu, Hung-Yu Kao


Abstract
This paper describes our approach for SemEval-2017 Task 8. We aim at detecting the stance of tweets and determining the veracity of the given rumor. We utilize a convolutional neural network for short text categorization using multiple filter sizes. Our approach beats the baseline classifiers on different event data with good F1 scores. The best of our submitted runs achieves rank 1st among all scores on subtask B.
Anthology ID:
S17-2081
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
465–469
Language:
URL:
https://www.aclweb.org/anthology/S17-2081
DOI:
10.18653/v1/S17-2081
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-2081.pdf