NLPZZX at SemEval-2018 Task 1: Using Ensemble Method for Emotion and Sentiment Intensity Determination

Zhengxin Zhang, Qimin Zhou, Hao Wu


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
Venue:
SemEval
SIGs:
SIGSEM | SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
116–122
Language:
URL:
https://aclanthology.org/S18-1015
DOI:
10.18653/v1/S18-1015
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/S18-1015.pdf