Emoji Are Not All Created Equal: The Effects of Emoji Variations on Brand Attitudes, Product Quality Expectations and Trial Intentions
Bibliographic record
Abstract
ABSTRACT Contributing to a burgeoning area of research on the nuanced effects of emojis in brand communications, the current research builds understanding of two dominant forms of emoji role—emojis as text reinforcement and emojis as text substitution—and their downstream effects. Across three studies, we examine how emoji roles differentially interact with message features to influence brand‐level outcomes (brand attitudes, product quality expectations and consumers' willingness to try a brand's product) through their effects on processing fluency. We find robust evidence that substitution emojis elicit more negative brand‐level outcomes than reinforcement emojis both when the emoji has low congruence with the text and when the complexity of the text in the message is high, and that these effects are mediated by processing fluency. These findings deepen our understanding of emojis' effects in brand communications and provide practical guidance for digital marketers regarding how to effectively leverage emojis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".