KDE-AFFECT at SemEval-2018 Task 1: Estimation of Affects in Tweet by Using Convolutional Neural Network for n-gram

Masaki Aono, Shinnosuke Himeno


Abstract
This paper describes our approach to SemEval-2018 Task1: Estimation of Affects in Tweet for 1a and 2a. Our team KDE-AFFECT employs several methods including one-dimensional Convolutional Neural Network for n-grams, together with word embedding and other preprocessing such as vocabulary unification and Emoji conversion into four emotional words.
Anthology ID:
S18-1022
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:
156–161
Language:
URL:
https://www.aclweb.org/anthology/S18-1022
DOI:
10.18653/v1/S18-1022
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1022.pdf