On the Context-Free Ambiguity of Emoji
This study addresses the challenge of emoji ambiguity for designers and users of digital communication, though it is incremental in nature.
The authors tackled the problem of measuring human agreement on emoji semantics without textual context by collecting a crowdsourced dataset of one-word descriptions for 1,289 emojis. They found that only 1.2% of emojis were completely unambiguous, while 4.3% were highly ambiguous, with most falling between these extremes.
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.