ArticleBehavioral sciences (Basel, Switzerland)2021
Understanding the Emotional Impact of GIFs on Instagram through Consumer Neuroscience.
Article in Behavioral sciences (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Neuro-insights: a systematic review of neuromarketing perspectives across consumer buying stages.Frontiers in neuroergonomics · 2025Pooled it
- Emojis in Marketing and Advertising: A Systematic Literature Review.Behavioral sciences (Basel, Switzerland) · 2025Review
- Consumers' Psychology Regarding Attachment to Social Media and Usage Frequency: A Mediated-Moderated Model.Behavioral sciences (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability of GIFs to generate emotionality in social media marketing strategies is analyzed. The aim of this work is to show how neuroscience research techniques can be integrated into the analysis of emotions, improving the results and helping to guide actions in social networks. This research is structured in two phases: an experimental study using automated biometric analysis (facial coding, GSR and eye tracking) and an analysis of declared feelings in the comments of Instagram users. Explicit valence, type of emotion, length of comment and proportion of emojis are extracted. The results indicate that the explicit measure of emotional valence shows a higher and more positive emotional level than the implicit one. This difference is influenced differently by the engagement and the proportion of emojis in the comment. A further step has been taken in the measurement of user emotionality in social media campaigns, including not only content analysis, but also providing new insights thanks to neuromarketing.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.