%0 Conference Proceedings %T Are Emojis Predictable? %A Barbieri, Francesco %A Ballesteros, Miguel %A Saggion, Horacio %Y Lapata, Mirella %Y Blunsom, Phil %Y Koller, Alexander %S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers %D 2017 %8 April %I Association for Computational Linguistics %C Valencia, Spain %F barbieri-etal-2017-emojis %X 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. %U https://aclanthology.org/E17-2017 %P 105-111