Título:
|
Are emojis predictable?
|
Autor/a:
|
Barbieri, Francesco; Ballesteros, Miguel; Saggion, Horacio
|
Abstract:
|
Comunicació presentada a la 15th Conference of the European Chapter of the Association for Computational Linguistics, celebrada els dies 3 a 7 d'abril de 2017 a València, Espanya. |
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 ShortTerm
Memory networks (LSTMs) in this
task. Our experimental results show that
our neural model outperforms two baselines
as well as humans solving the same
task, suggesting that computational models
are able to better capture the underlying
semantics of emojis. |
Abstract:
|
First and third authors acknowledge support from the TUNER project (TIN2015-65308-C5-5-R, MINECO/FEDER, UE) and the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502). |
Materia(s):
|
-Tractament del llenguatge natural (Informàtica) |
Derechos:
|
© ACL, Creative Commons Attribution 4.0 License
http://creativecommons.org/licenses/by/4.0/ |
Tipo de documento:
|
Objeto de conferencia Artículo - Versión publicada |
Editor:
|
ACL (Association for Computational Linguistics)
|
Compartir:
|
|