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
Editors:
Mirella Lapata, Phil Blunsom, Alexander Koller
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
105–111
Language:
URL:
https://aclanthology.org/E17-2017
DOI:
Bibkey:
Cite (ACL):
Francesco Barbieri, Miguel Ballesteros, and Horacio Saggion. 2017. Are Emojis Predictable?. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 105–111, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Are Emojis Predictable? (Barbieri et al., EACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/E17-2017.pdf
Code
 additional community code
Data
Multimodal Emoji Prediction