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Record W4361272692 · doi:10.1177/09760911231159690

An Exploration of Social Media Users’ Desires to Become Social Media Influencers

2023· article· en· W4361272692 on OpenAlexaff
Sheldon Fetter, Paige Coyne, Samantha Monk, Sarah J. Woodruff

Bibliographic record

VenueMedia Watch · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsInfluencer marketingPerceptionSocial mediaPsychologyAdvertisingSocial psychologyBusinessMarketingComputer science

Abstract

fetched live from OpenAlex

With increased social media (SM) use, users are becoming frequently more exposed to SM influencers. This study aimed to explore SM influencer aspirations among young adults, specifically investigating the desire and rationale to become a SM influencer. Moreover, aspirations of becoming a SM influencer were explored by perceptions of SM influencers and SM use. The sample included 769 young Canadians (aged 16–30) who were mainly women ( n = 599, 79%). Overall, 29 (4%) participants considered themselves to be SM influencers, whereas 579 (75%) participants reported that they wanted to ( maybe or yes) become a SM influencer. The top three reasons for wanting to be an influencer were money, the opportunity to try new products or services, and it’s fun work. In addition, having certain perceptions of SM influencers (e.g., knowing an influencer, or having been influenced) significantly predicted the desire to be a SM influencer ( p < 0.001). Moreover, certain SM usage patterns (e.g., time spent on SM) significantly predicted the desire to be a SM influencer ( p < 0.001). These findings could help researchers understand the impact of SM influencers on their followers and the potential reasons why SM users aspire to become SM influencers themselves.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.366
Teacher spread0.271 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations11
Published2023
Admission routes1
Has abstractyes

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