Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification

Alon Rozental, Daniel Fleischer


Abstract
This paper describes the participation of Amobee in the shared sentiment analysis task at SemEval 2018. We participated in all the English sub-tasks and the Spanish valence tasks. Our system consists of three parts: training task-specific word embeddings, training a model consisting of gated-recurrent-units (GRU) with a convolution neural network (CNN) attention mechanism and training stacking-based ensembles for each of the sub-tasks. Our algorithm reached the 3rd and 1st places in the valence ordinal classification sub-tasks in English and Spanish, respectively.
Anthology ID:
S18-1033
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
218–225
Language:
URL:
https://www.aclweb.org/anthology/S18-1033
DOI:
10.18653/v1/S18-1033
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1033.pdf