@InProceedings{yu-EtAl:2017:I17-4,
  author    = {Yu, Liang-Chih  and  Lee, Lung-Hao  and  Wang, Jin  and  Wong, Kam-Fai},
  title     = {IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases},
  booktitle = {Proceedings of the IJCNLP 2017, Shared Tasks},
  month     = {December},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {9--16},
  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.},
  url       = {http://www.aclweb.org/anthology/I17-4002}
}