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. ...
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.
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