AffecThor at SemEval-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets

Mostafa Abdou, Artur Kulmizev, Joan Ginés i Ametllé


Abstract
In this paper we describe our submission to SemEval-2018 Task 1: Affects in Tweets. The model which we present is an ensemble of various neural architectures and gradient boosted trees, and employs three different types of vectorial tweet representations. Furthermore, our system is language-independent and ranked first in 5 out of the 12 subtasks in which we participated, while achieving competitive results in the remaining ones. Comparatively remarkable performance is observed on both the Arabic and Spanish languages.
Anthology ID:
S18-1032
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:
210–217
Language:
URL:
https://www.aclweb.org/anthology/S18-1032
DOI:
10.18653/v1/S18-1032
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1032.pdf