# On the Context-Free Ambiguity of Emoji

arXiv: https://arxiv.org/abs/2201.06302 · HTML: https://mlsanity.com/paper/2201.06302/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 29 references that are in the map.
- First posted on arXiv 17 Jan 2022.

## Builds on (most cited first, 9 of 9)

- [Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm](https://mlsanity.com/paper/1708.00524/) (2017)
- [Sentiment of Emojis](https://mlsanity.com/paper/1509.07761/) (2015)
- [emoji2vec: Learning Emoji Representations from their Description](https://mlsanity.com/paper/1609.08359/) (2016)
- [EmojiNet: An Open Service and API for Emoji Sense Discovery](https://mlsanity.com/paper/1707.04652/) (2017)
- [I Stand With You: Using Emojis to Study Solidarity in Crisis Events](https://mlsanity.com/paper/1907.08326/) (2019)
- [Exploring Emoji Usage and Prediction Through a Temporal Variation Lens](https://mlsanity.com/paper/1805.00731/) (2018)
- [Semantic Journeys: Quantifying Change in Emoji Meaning from 2012-2018](https://mlsanity.com/paper/2105.00846/) (2021)
- [Identity Signals in Emoji Do not Influence Perception of Factual Truth on Twitter](https://mlsanity.com/paper/2105.03160/) (2021)
- [The Shadowy Lives of Emojis: An Analysis of a Hacktivist Collective's Use of Emojis on Twitter](https://mlsanity.com/paper/2105.03168/) (2021)

## Built on by (most cited first, 4 of 4)

- [Irony in Emojis: A Comparative Study of Human and LLM Interpretation](https://mlsanity.com/paper/2501.11241/) (2025)
- [A Cognitive Account of the Puzzle of Ideography](https://mlsanity.com/paper/2305.00296/) (2023)
- [Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation](https://mlsanity.com/paper/2404.01070/) (2024)
- [The Prosody of Emojis](https://mlsanity.com/paper/2508.00537/) (2025)

## Abstract (arXiv)

Emojis come with prepacked semantics making them great candidates to create new forms of more accessible communications. Yet, little is known about how much of this emojis semantic is agreed upon by humans, outside of textual contexts. Thus, we collected a crowdsourced dataset of one-word emoji descriptions for 1,289 emojis presented to participants with no surrounding text. The emojis and their interpretations were then examined for ambiguity. We find that with 30 annotations per emoji, 16 emojis (1.2%) are completely unambiguous, whereas 55 emojis (4.3%) are so ambiguous that their descriptions are indistinguishable from randomly chosen descriptions. Most of studied emojis are spread out between the two extremes. Furthermore, investigating the ambiguity of different types of emojis, we find that an important factor is the extent to which an emoji has an embedded symbolical meaning drawn from an established code-book of symbols. We conclude by discussing design implications.