Evidence map›Paper›PMID 40642172›Full record

ArticleFrontiers in nutrition2025

Food neophobia: psychological dimensions of consumer perception and emotional sentiment in social media discourse.

Yu Shan, Hong Wang, Wenqi Wang

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Yu ShanSchool of Management Science, Chengdu University of Technology, Sichuan, China.
Hong WangSchool of Business, Chengdu University of Technology, Chengdu, Sichuan, China.
Wenqi WangSchool of Management Science, Chengdu University of Technology, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Addressing global food security necessitates exploring future foods, yet their societal acceptance hinges critically on public perception an2d psychological barriers such as neophobia. This study delves into the psychological dimensions underlying consumer perception of future foods, investigating the intricate relationship between food neophobia and these perceptions, and mapping the prevailing emotional landscape surrounding novel food adoption. Employing a Social Media Analytics (SMA) framework to capture ecologically valid public discourse, we utilized social media text analysis, integrating topic modeling and sentiment analysis, to dissect online expressions concerning future foods. Our analysis reveals that public evaluations are predominantly positive (53.20%), while a substantial segment expresses negative sentiments (30.48%) and ambivalence (16.32%). Psychologically, we identified four salient perceptual dimensions - taste, appearance, culture, and technology - which differentially mediate food neophobia and elicit distinct emotional valences. Notably, appearance and cultural perceptions are associated with heightened neophobia and negative emotional responses, suggesting underlying psychological mechanisms of sensory and socio-cultural rejection. These findings offer critical psychological insights for future food producers and policymakers, highlighting the psychological determinants of public attitudes toward future foods and informing psychologically-informed strategies to enhance consumer acceptance and promote dietary innovation.

Indexed as

future foodsLatent Dirichlet Allocation (LDA)neophobiaperception of future foodssocial media analytics (SMA)

Identifiers

PMID40642172
PMCPMC12243030

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.