Abstract
In this paper, we put forward a system that competed at SemEval-2018 Task 1: “Affect in Tweets”. Our system uses a simple yet effective ensemble method which combines several neural network components. We participate in two subtasks for English tweets: EI-reg and V-reg. For two subtasks, different combinations of neural components are examined. For EI-reg, our system achieves an accuracy of 0.727 in Pearson Correlation Coefficient (all instances) and an accuracy of 0.555 in Pearson Correlation Coefficient (0.5-1). For V-reg, the achieved accuracy scores are respectively 0.835 and 0.670- Anthology ID:
- S18-1015
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 116–122
- Language:
- URL:
- https://aclanthology.org/S18-1015
- DOI:
- 10.18653/v1/S18-1015
- Cite (ACL):
- Zhengxin Zhang, Qimin Zhou, and Hao Wu. 2018. NLPZZX at SemEval-2018 Task 1: Using Ensemble Method for Emotion and Sentiment Intensity Determination. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 116–122, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- NLPZZX at SemEval-2018 Task 1: Using Ensemble Method for Emotion and Sentiment Intensity Determination (Zhang et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/S18-1015.pdf