Tweety at SemEval-2018 Task 2: Predicting Emojis using Hierarchical Attention Neural Networks and Support Vector Machine

Daniel Kopev, Atanas Atanasov, Dimitrina Zlatkova, Momchil Hardalov, Ivan Koychev, Ivelina Nikolova, Galia Angelova


Abstract
We present the system built for SemEval-2018 Task 2 on Emoji Prediction. Although Twitter messages are very short we managed to design a wide variety of features: textual, semantic, sentiment, emotion-, and color-related ones. We investigated different methods of text preprocessing including replacing text emojis with respective tokens and splitting hashtags to capture more meaning. To represent text we used word n-grams and word embeddings. We experimented with a wide range of classifiers and our best results were achieved using a SVM-based classifier and a Hierarchical Attention Neural Network.
Anthology ID:
S18-1080
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:
497–501
Language:
URL:
https://www.aclweb.org/anthology/S18-1080
DOI:
10.18653/v1/S18-1080
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1080.pdf