Overview of the IALP 2016 Shared Task on Dimensional Sentiment Analysis for Chinese Words

被引：0

作者：

Yu, Liang-Chih ^{[1
,2
]}

Lee, Lung-Hao ^{[3
]}

Wong, Kam-Fai ^{[4
]}

机构：

[1] Yuan Ze Univ, Dept Informat Management, Taoyuan, Taiwan

[2] Yuan Ze Univ, Innovat Ctr Big Data & Digital Convergence, Taoyuan, Taiwan

[3] Natl Taiwan Normal Univ, Grad Inst Lib & Informat Studies, Taipei, Taiwan

[4] Chinese Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China

来源：

PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP) | 2016年

关键词：

dimensional sentiment analysis; valence-arousal space; affective computing;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents the IALP 2016 shared task on Dimensional Sentiment Analysis for Chinese Words (DSAW) which seeks to identify a real-value sentiment score of Chinese words in the both valence and arousal dimensions. Valence represents the degree of pleasant and unpleasant (or positive and negative) feelings, and arousal represents the degree of excitement and calm. Of the 22 teams registered for this shared task for two-dimensional sentiment analysis, 16 submitted results. We expected that this evaluation campaign could produce more advanced dimensional sentiment analysis techniques, especially for Chinese affective computing. All data sets with gold standards and scoring script are made publicly available to researchers.

引用

页码：156 / 160

页数：5

共 32 条

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