Exploring Emoji Usage and Prediction Through a Temporal Variation Lens

Francesco Barbieri, Luis Marujo, Pradeep Karuturi, William Brendel, Horacio Saggion
Event ICWSM 2018 (Workshop)
Research Areas Natural Language Processing, Deep Learning, Human Computer Interaction

Abstract: The frequent use of Emojis on social media platforms has created a new form of multimodal social interaction. Developing methods for the study and representation of emoji semantics helps to improve future multimodal communication systems. In this paper we explore the usage and semantics of emojis over time. We compare emoji embeddings trained on a corpus of different seasons and show that some emojis are used differently depending on the time of the year. Moreover, we propose a method to take into account the time information for emoji prediction systems, outperforming state-of-the-art systems. We show that, using the time information, the accuracy of some emojis can be significantly improved.