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Discourse anaphoricity vs. perspective sensitivity in emoji semantics

Paper · 2023 · Patrick Georg Grosz, Elsi Kaiser and Francesco Pierini

Summary

The paper asks how emoji combine with the text around them and argues that two families behave in semantically different ways. Affective face emoji (yellow-disc faces showing emotions) act like expressives. They are tied to an attitude holder, by default the author, and they comment on a proposition drawn from the message. Activity emoji (objects or people that stand for doing something, such as ⚽ for playing football) work as event descriptions. They form their own discourse unit, much like a free adjunct, and their agent is resolved anaphorically through discourse coherence. The evidence comes from introspective judgments, anonymized naturally occurring Twitter posts, and experimental work. Negation provides a key diagnostic. Neither class normally falls under clausal negation. Activity emoji only seem to do so when linked to the text by an Explanation relation. Face emoji do so when the default reading would be pragmatically odd, or in a construction where faces repeatedly alternate with words. The authors also sketch iconic, lexicalist meaning schemas. The classification is meant as groundwork for formal emoji semantics.

Key points

  • Two contrasting properties are proposed: face emoji show perspective sensitivity, preferring a first-person anchor, while activity emoji show discourse anaphoricity in how their agent is identified.
  • Activity emoji are defined by function rather than by Unicode category. For example, 🍕 counts as an activity emoji when it means eating pizza, even though Unicode files it under Food & Drink.
  • Negation diagnostic:
    • Both classes generally take scope outside negation.
    • Activity emoji appear to scope under negation only with an Explanation discourse relation.
    • Face emoji appear to do so when the default reading is infelicitous, or in the emoji-repetition construction, where the alternation itself marks scope.
  • A schematic iconic lexical entry covers all face emoji: the author holds an emotional attitude toward p that matches the depicted face. Activity emoji get a similar schema as a set of emoji-based eventualities, in three versions:
    • a richer variant that encodes the agent;
    • a middle variant with eventualities only;
    • a minimal variant that denotes a property.
  • Ethics: Twitter use was approved by the Norwegian Centre for Research Data (NSD, ref. 414,881). User names and URLs were removed, and personal names were replaced with John or Smith. The paper is an expanded version of a Sinn und Bedeutung 25 proceedings paper.

Interesting ideas

  • I1. Non-verbal tokens should be split by semantic type rather than treated as one class: some express the author's attitude, others describe events that need an agent.
  • I2. An activity emoji can be read as a separate clause-like unit whose agent is found through coherence relations, much like resolving the implicit subject of a free adjunct.
  • I3. Interaction with negation can serve as a diagnostic: checking whether an element falls inside or outside the scope of negation reveals whether it is not-at-issue commentary or part of the asserted content.
  • I4. A single schematic lexical rule can generate entries for a whole open class: one template with a slot for the symbol replaces storing each emoji separately.
  • I5. Corpus examples can be kept verbatim for linguistic integrity while identity is removed: handles and URLs are stripped and person names replaced with fixed placeholders.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (tokens): The tagger could give emoji a feature such as Affective vs. Activity, so that later stages know whether to attach the emoji to the author's stance or build an event from it.
  • I2 (frames): Coreference and frame building could create an event frame for the emoji with an empty agent slot, then fill it from the discourse relation it most plausibly has with the neighbouring clause.
  • I3 (frames): Pragmatics could use this test to keep author attitudes (expressives, emoji, evaluative particles) out of the negated proposition and avoid wrongly flipping their polarity.
  • I4 (world): The compiled knowledge layer could hold one rule that maps any face emoji to an author-attitude state toward the current proposition, instead of a hand-listed table.
  • I5 (learn): Social-media text gathered for silver data or evaluation could be anonymized the same way, replacing names consistently so that coreference chains stay intact.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of Southern CaliforniaLos Angeles · United States162 works · 35,836 citations🎓University of OsloOslo · Norway51 works · 4,155 citations🔬École Normale Supérieure - PSLParis · France23 works · 4,357 citations🎓Université Paris Sciences et LettresParis · France21 works · 3,290 citations🔬École des hautes études en sciences socialesParis · France15 works · 2,302 citations🔬Institut Jean NicodParis · France11 works · 1,659 citations

 Fields, topics and concepts

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksHuman-Computer Interaction · 141 works

🧭 Topics 1Research subjects and languages the work is about.Discourse analysis · 466 works

Cite

Cite as Patrick Georg Grosz, Elsi Kaiser and Francesco Pierini. 2023. Discourse anaphoricity vs. perspective sensitivity in emoji semantics. Glossa: a journal of general linguistics.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.16995/glossa.9128

@article{grosz2023discourse,
  title = {{Discourse anaphoricity vs. perspective sensitivity in emoji semantics}},
  author = {Patrick Georg Grosz, Elsi Kaiser and Francesco Pierini},
  journal = {Glossa: a journal of general linguistics},
  year = {2023},
  doi = {10.16995/glossa.9128},
  url = {https://doi.org/10.16995/glossa.9128}
}

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