- Anthology ID:
- S16-1040
- Volume:
- Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
- Month:
- June
- Year:
- 2016
- Address:
- San Diego, California
- Editors:
- Steven Bethard, Marine Carpuat, Daniel Cer, David Jurgens, Preslav Nakov, Torsten Zesch
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 256–261
- Language:
- URL:
- https://aclanthology.org/S16-1040
- DOI:
- 10.18653/v1/S16-1040
- Cite (ACL):
- Yunxiao Zhou, Zhihua Zhang, and Man Lan. 2016. ECNU at SemEval-2016 Task 4: An Empirical Investigation of Traditional NLP Features and Word Embedding Features for Sentence-level and Topic-level Sentiment Analysis in Twitter. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pages 256–261, San Diego, California. Association for Computational Linguistics.
- Cite (Informal):
- ECNU at SemEval-2016 Task 4: An Empirical Investigation of Traditional NLP Features and Word Embedding Features for Sentence-level and Topic-level Sentiment Analysis in Twitter (Zhou et al., SemEval 2016)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/S16-1040.pdf