Exploring Emoji Usage and Prediction Through a Temporal Variation Lens

TL;DR

This paper investigates how emoji usage varies over time on social media and introduces a time-aware prediction method that improves emoji prediction accuracy by considering temporal patterns.

Contribution

It presents a novel approach to incorporate temporal information into emoji prediction models, enhancing their performance over existing methods.

Findings

Emoji usage varies seasonally and contextually.

Time-aware models outperform state-of-the-art emoji prediction systems.

Temporal features significantly improve emoji prediction accuracy.

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.