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Record W4311858058 · doi:10.54097/fbem.v6i3.3462

Research on the Influence of Emoji in Advertising Slogans on Consumers' Purchase Intention

2022· article· en· W4311858058 on OpenAlexaff
Yeting Shen

Bibliographic record

VenueFrontiers in Business Economics and Management · 2022
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsEarl Haig Secondary School
Fundersnot available
KeywordsEmojiAdvertisingProduct (mathematics)BusinessPsychologyMarketingSocial mediaComputer scienceMathematicsWorld Wide Web

Abstract

fetched live from OpenAlex

In the Internet era emoji are being used more and more frequently, this study focuses on how the use of emoji in product advertising slogans affects consumers' purchase intentions. We conducted 2 experiments to explore this issue. Experiment 1 found that adding emoji to product advertisements would increase consumers' willingness to buy products, and the effect was mediated by psychological simulation. Based on this, Experiment 2 further found that the position of the emoji in the tagline would have a moderating effect, i.e., the emoji would increase purchase intention only when the emoji was in the middle of the tagline, while the emoji's effect on purchase intention disappeared when the emoji was on both sides (left or right). This study makes some theoretical contributions and practical contributions to how emoji can be used in the consumer market.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.025
GPT teacher head0.264
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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