Communicating data insights in an accessible and engaging manner to a broader audience remains a significant challenge. To address this problem, we introduce the Emoji Encoder, a tool that generates a set of emoji recommendations for the field and category names appearing in a tabular dataset. The selected set of emoji encodings can be used to generate configurable unit charts that combine plain text and emojis as word-scale graphics. These charts can serve to contrast values across multiple quantitative fields for each row in the data or to communicate trends over time. Any resulting chart is simply a block of text characters, meaning that it can be directly copied into a text message or posted on a communication platform such as Slack or Teams. This work represents a step toward our larger goal of developing novel, fun, and succinct data storytelling experiences that engage those who do not identify as data analysts. Emoji-based unit charts can offer contextual cues related to the data at the center of a conversation on platforms where emoji-rich communication is typical.
@article{arxiv.2408.13418,
title = {The Data-Wink Ratio: Emoji Encoder for Generating Semantically-Resonant Unit Charts},
author = {Matthew Brehmer and Vidya Setlur and Zoe and Michael Correll},
journal= {arXiv preprint arXiv:2408.13418},
year = {2024}
}
Comments
To appear IEEE VIS 2024 Workshop on Data Storytelling in an Era of Generative AI (Gen4DS): https://gen4ds.github.io/gen4ds/