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

2017-12-01 · IJCNLP 2017 12 · Jui-Feng Yeh, Jian-Cheng Tsai, Bo-Wei Wu, Tai-You Kuang

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.

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Tasks

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