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        <title>IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases</title>
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        <namePart type="given">Liang-Chih</namePart>
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        <namePart type="given">Kam-Fai</namePart>
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    <abstract>This paper presents the IJCNLP 2017 shared task on Dimensional Sentiment Analysis for Chinese Phrases (DSAP) which seeks to identify a real-value sentiment score of Chinese single words and multi-word phrases 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 19 teams registered for this shared task for two-dimensional sentiment analysis, 13 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.</abstract>
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%0 Conference Proceedings
%T IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases
%A Yu, Liang-Chih
%A Lee, Lung-Hao
%A Wang, Jin
%A Wong, Kam-Fai
%Y Liu, Chao-Hong
%Y Nakov, Preslav
%Y Xue, Nianwen
%S Proceedings of the IJCNLP 2017, Shared Tasks
%D 2017
%8 December
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F yu-etal-2017-ijcnlp
%X This paper presents the IJCNLP 2017 shared task on Dimensional Sentiment Analysis for Chinese Phrases (DSAP) which seeks to identify a real-value sentiment score of Chinese single words and multi-word phrases 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 19 teams registered for this shared task for two-dimensional sentiment analysis, 13 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.
%U https://aclanthology.org/I17-4002
%P 9-16

Markdown (Informal)

[IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases](https://aclanthology.org/I17-4002) (Yu et al., IJCNLP 2017)

• IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases (Yu et al., IJCNLP 2017)

ACL

• Liang-Chih Yu, Lung-Hao Lee, Jin Wang, and Kam-Fai Wong. 2017. IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases. In Proceedings of the IJCNLP 2017, Shared Tasks, pages 9–16, Taipei, Taiwan. Asian Federation of Natural Language Processing.