From Emoji Usage to Categorical Emoji Prediction

Abstract : Emoji usage drastically increased recently, they are becoming some of the most common ways to convey emotions and sentiments in social messaging applications. Several research works automatically recommend emojis, so users do not have to go through a library of thousands of emojis. In order to improve emoji recommendation, we present and distribute two useful resources: an emoji embedding model from real usage, and emoji clustering based on these embeddings to automatically identify groups of emojis. Assuming that emojis are part of written natural language and can be considered as words, we only used unsu-pervised learning methods to extract patterns and knowledge from real emoji usage in tweets. Thereby, emotion categories of face emojis were obtained directly from text in a fully reproductible way. These resources and methodology have multiple usages; for example, they could be used to improve our understanding of emojis or enhance emoji recommendation .
Type de document :
Communication dans un congrès
19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLING 2018), Mar 2018, Hanoï, Vietnam. 〈https://www.cicling.org/2018/〉
Liste complète des métadonnées

Littérature citée [16 références]  Voir  Masquer  Télécharger

https://hal-amu.archives-ouvertes.fr/hal-01871045
Contributeur : Gaël Guibon <>
Soumis le : lundi 10 septembre 2018 - 11:35:59
Dernière modification le : mardi 26 février 2019 - 21:49:58
Document(s) archivé(s) le : mardi 11 décembre 2018 - 14:05:22

Fichier

cicling2-cameraready-fixed.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01871045, version 1

Collections

Citation

Gaël Guibon, Magalie Ochs, Patrice Bellot. From Emoji Usage to Categorical Emoji Prediction. 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLING 2018), Mar 2018, Hanoï, Vietnam. 〈https://www.cicling.org/2018/〉. 〈hal-01871045〉

Partager

Métriques

Consultations de la notice

72

Téléchargements de fichiers

154