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The Data-Wink Ratio: Emoji Encoder for Generating Semantically-Resonant Unit Charts

Matthew Brehmer, Vidya Setlur, Zoe, Michael Correll

TL;DR

The paper tackles the challenge of conveying data insights to broad, text-based audiences by introducing the Emoji Encoder, a Tableau extension that automatically generates semantically resonant emoji palettes for dataset fields and values to produce plain-text unit charts and time-series visuals. It employs Word2Vec embeddings trained on Emojipedia to map field names and categories to emoji recommendations, enabling authors to configure and export charts that can be pasted into text channels like Slack or Teams. Key contributions include an interactive inspector for ranking and overriding emoji choices, support for both multivariate unit charts and univariate time-series, and a workflow that integrates emoji-based visuals directly into dashboards and text-based communications. The work aims to boost accessible, playful data storytelling for non-analysts and outlines a path toward broader emoji representations, narrative augmentation with language models, and human-centered evaluations to assess usability and readability of emoji-rich charts.

Abstract

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.

The Data-Wink Ratio: Emoji Encoder for Generating Semantically-Resonant Unit Charts

TL;DR

The paper tackles the challenge of conveying data insights to broad, text-based audiences by introducing the Emoji Encoder, a Tableau extension that automatically generates semantically resonant emoji palettes for dataset fields and values to produce plain-text unit charts and time-series visuals. It employs Word2Vec embeddings trained on Emojipedia to map field names and categories to emoji recommendations, enabling authors to configure and export charts that can be pasted into text channels like Slack or Teams. Key contributions include an interactive inspector for ranking and overriding emoji choices, support for both multivariate unit charts and univariate time-series, and a workflow that integrates emoji-based visuals directly into dashboards and text-based communications. The work aims to boost accessible, playful data storytelling for non-analysts and outlines a path toward broader emoji representations, narrative augmentation with language models, and human-centered evaluations to assess usability and readability of emoji-rich charts.

Abstract

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.
Paper Structure (4 sections, 1 figure)

This paper contains 4 sections, 1 figure.

Table of Contents

  1. Introduction
  2. Background & Related Work
  3. Emoji Encoder
  4. Discussion & Future Work

Figures (1)

  • Figure 1: In contrast to the unit chart specification (c.f. \ref{['fig:teaser']}.1.b), the Emoji Encoder can also be used to represent univariate time series, such as in this instance depicting global average temperature differences over ten-year intervals between 1918 and 2018 using our emoji-10 scale: .