@InProceedings{chen-chen-ku:2017:I17-4,
  author    = {chen, szu-min  and  Chen, Zi-Yuan  and  Ku, Lun-Wei},
  title     = {NLPSA at IJCNLP-2017 Task 2: Imagine Scenario: Leveraging Supportive Images for Dimensional Sentiment Analysis},
  booktitle = {Proceedings of the IJCNLP 2017, Shared Tasks},
  month     = {December},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {105--111},
  abstract  = {Categorical sentiment classification has drawn much attention in the field of
	NLP, while less work has been conducted for dimensional sentiment analysis
	(DSA). Recent works for DSA utilize either word embedding, knowledge base
	features, or bilingual language resources. In this paper, we propose our model
	for IJCNLP 2017 Dimensional Sentiment Analysis for Chinese Phrases shared task.
	Our model incorporates word embedding as well as image features, attempting to
	simulate human's imaging behavior toward sentiment analysis. Though the
	performance is not comparable to others in the end, we conduct several
	experiments with possible reasons discussed, and analyze the drawbacks of our
	model.},
  url       = {http://www.aclweb.org/anthology/I17-4017}
}