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.- Anthology ID:
- I17-4017
- Volume:
- Proceedings of the IJCNLP 2017, Shared Tasks
- Month:
- December
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 105–111
- Language:
- URL:
- https://aclanthology.org/I17-4017
- DOI:
- Cite (ACL):
- Szu-Min Chen, Zi-Yuan Chen, and Lun-Wei Ku. 2017. NLPSA at IJCNLP-2017 Task 2: Imagine Scenario: Leveraging Supportive Images for Dimensional Sentiment Analysis. In Proceedings of the IJCNLP 2017, Shared Tasks, pages 105–111, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- NLPSA at IJCNLP-2017 Task 2: Imagine Scenario: Leveraging Supportive Images for Dimensional Sentiment Analysis (Chen et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/I17-4017.pdf