Lexicalization and compositionality of emoji

  • Neil Cohn (Creator)
  • Benjamin Weissman (Creator)
  • Jan Engelen (Creator)
  • Lena Thamsen (Creator)
  • Elise Baas (Creator)

Dataset

Description

Emoji have been ubiquitous in communication for over a decade, yet how they derive meaning remains underexplored. Here we examine two aspects fundamental to linguistic meaning-making: the degree to which emoji have conventional lexicalized meanings (Experiments 1 & 2) and whether their combination allows for compositional meaning-making in linear strings compared to spatial pictures (Experiment 3). Experiment 1 established that participants have a range of agreement for the conventional meanings of emoji. Across Experiments 2 and 3, we measured accuracy and response times to word-emoji pairings in a match/mismatch task. In Experiment 2, we found that accuracy and response time both correlate significantly with the level of population-wide meaning agreement, suggesting that lexical access of single emoji may be comparable to that of words. In Experiment 3, however, presenting emoji-only expressions in a linear, written language-like sentence order incurred a processing cost compared to presenting the same expressions in a nonlinear analog depiction. Altogether, these findings suggest that emoji can allow a range of stored, lexicalized representations, yet they remain constrained in their combinatorial properties.
Date made available14 Apr 2022
PublisherDataverseNL

Cite this