Evidence map›Paper›PMID 41311700›Full record

ArticleFrontiers in neuroscience2025

Are emojis better? The impact of generative AI emoji cues and service outcomes on user satisfaction: evidence from ERPs.

Ruxia Cheng, Rui Sun, Dong Lv, Qiuhua Zhu

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ruxia ChengSchool of Business Administration, Huaqiao University, Quanzhou, China.
Rui SunSchool of Business Administration, Huaqiao University, Quanzhou, China.
Dong LvSchool of Business Administration, Huaqiao University, Quanzhou, China.
Qiuhua ZhuChen Shouren Business School, Quanzhou Normal University, Quanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To promote the sustainable development of Generative Artificial Intelligence (GenAI) applications in the service industry, enhancing user satisfaction is key. Emojis serve as catalysts for conveying emotions and enhancing user experience in online communication. However, due to the black-box nature and unpredictability of GenAI, service providers find it challenging to control the boundaries of their application. Currently, there is ongoing debate within the academic community regarding the use of emojis in GenAI, particularly concerning emotional manipulation and experience enhancement, with further exploration needed into their effectiveness and underlying mechanisms. This study is based on the emotion as social information model and employs event-related potential (ERP) technology with high temporal resolution, which is more suitable for GenAI interaction scenarios. By measuring users' immediate cognitive processing and psychological activities, the study analyzes the underlying cognitive neural mechanisms through which emojis (presence vs. absence) and service outcomes (success vs. failure) influence user satisfaction. Behavioral results indicate that the outcome of GenAI services determines user satisfaction, while the presence or absence of emojis does not directly impact satisfaction. ERP results show that the presence of emojis compared to their absence triggers larger P3 amplitudes (emotional arousal) and N4 amplitudes (cognitive conflict); compared to service success, the presence of emojis during service failure triggers larger N4 amplitudes. This study reveals the complexity of user responses in real human-machine interaction environments, enriches research on the use of Emojis in GenAI, and provides scientific theoretical and practical foundations for GenAI design and enhancing user experience.

Indexed as

emojievent-related potentialsgenerative artificial intelligencesatisfactionservice outcome

Identifiers

PMID41311700
PMCPMC12647028

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.