NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations

Jui-Feng Yeh, Jian-Cheng Tsai, Bo-Wei Wu, Tai-You Kuang


Abstract
This paper presents two vector representations proposed by National Chiayi University (NCYU) about phrased-based sentiment detection which was used to compete in dimensional sentiment analysis for Chinese phrases (DSACP) at IJCNLP 2017. The vector-based sentiment phraselike unit analysis models are proposed in this article. E-HowNet-based clustering is used to obtain the values of valence and arousal for sentiment words first. An out-of-vocabulary function is also defined in this article to measure the dimensional emotion values for unknown words. For predicting the corresponding values of sentiment phrase-like unit, a vectorbased approach is proposed here. According to the experimental results, we can find the proposed approach is efficacious.
Anthology ID:
I17-4018
Volume:
Proceedings of the IJCNLP 2017, Shared Tasks
Month:
December
Year:
2017
Address:
Taipei, Taiwan
Venue:
IJCNLP
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
112–117
Language:
URL:
https://www.aclweb.org/anthology/I17-4018
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/I17-4018.pdf