Are Emojis Predictable?

Francesco Barbieri, Miguel Ballesteros, Horacio Saggion


Abstract
Emojis are ideograms which are naturally combined with plain text to visually complement or condense the meaning of a message. Despite being widely used in social media, their underlying semantics have received little attention from a Natural Language Processing standpoint. In this paper, we investigate the relation between words and emojis, studying the novel task of predicting which emojis are evoked by text-based tweet messages. We train several models based on Long Short-Term Memory networks (LSTMs) in this task. Our experimental results show that our neural model outperforms a baseline as well as humans solving the same task, suggesting that computational models are able to better capture the underlying semantics of emojis.
Anthology ID:
E17-2017
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
105–111
Language:
URL:
https://www.aclweb.org/anthology/E17-2017
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/E17-2017.pdf