# Time to Take Emoji Seriously: They Vastly Improve Casual Conversational Models

arXiv: https://arxiv.org/abs/1910.13793 · HTML: https://mlsanity.com/paper/1910.13793/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Oct 2019.

## Built on by (most cited first, 1 of 1)

- [Modeling offensive content detection for TikTok](https://mlsanity.com/paper/2408.16857/) (2024)

## Abstract (arXiv)

Graphical emoji are ubiquitous in modern-day online conversations. So is a single thumbs-up emoji able to signify an agreement, without any words. We argue that the current state-of-the-art systems are ill-equipped to correctly interpret these emoji, especially in a conversational context. However, in a casual context, the benefits might be high: a better understanding of users' utterances and more natural, emoji-rich responses. With this in mind, we modify BERT to fully support emoji, both from the Unicode Standard and custom emoji. This modified BERT is then trained on a corpus of question-answer (QA) tuples with a high number of emoji, where we're able to increase the 1-of-100 accuracy from 12.7% for the current state-of-the-art to 17.8% for our model with emoji support.