Comunicació presentada a la Tenth International Conference on Language Resources and Evaluation (LREC 2016), celebrada els dies 23 a 28 de maig de 2016 a Portorož, Eslovènia.

Emojis allow us to describe objects, situations and even feelings with small images, providing a visual and quick way to communicate. In this paper, we analyse emojis used in Twitter with distributional semantic models. We retrieve 10 millions tweets posted by USA users, and we build several skip gram word embedding models by mapping in the same vectorial space both words and emojis. We test our models with semantic similarity experiments, comparing the output of our models with human assessment. We also carry out an exhaustive qualitative evaluation, showing interesting results.

This work is (partly) supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502). The second and third author acknowledge support from the EU project Dr. Inventor (FP7-ICT-2013.8.1 project number 611383).