Year: 2016
Type: conference-paper
Abstract: 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.
Institution: Universitat Pompeu Fabra
Language: English
Subfield: Linguistics and Language
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Awards: G3402147602, G6932722290
OpenAlex ID: W2571906210
