XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter

Yazhou Hao, YangYang Lan, Yufei Li, Chen Li

Abstract
This paper describes the XJSA System submission from XJTU. Our system was created for SemEval2017 Task 4 – subtask A which is very popular and fundamental. The system is based on convolutional neural network and word embedding. We used two pre-trained word vectors and adopt a dynamic strategy for k-max pooling.
Anthology ID:
S17-2122
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
728–731
Language:
URL:
https://aclanthology.org/S17-2122
DOI:
10.18653/v1/S17-2122
Bibkey:
Cite (ACL):
Yazhou Hao, YangYang Lan, Yufei Li, and Chen Li. 2017. XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 728–731, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter (Hao et al., SemEval 2017)
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https://preview.aclanthology.org/nschneid-patch-1/S17-2122.pdf
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