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A PRESENÇA DIGITAL NO INSTAGRAM DA MARCA ADIDAS EM 2017

2019· article· en· W3012359009 on OpenAlexaff
Taís Steffenello Ghisleni, Nathane Spencer Trindade

Bibliographic record

VenueCadernos de Educação Tecnologia e Sociedade · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsTestimonialSocial mediaDigital mediaPeriod (music)AdvertisingSociologyArtBusinessComputer scienceWorld Wide WebAesthetics

Abstract

fetched live from OpenAlex

This project analyzes the digital presence of Adidas Brasil and Adidas Originals in 2017 on Instagram, covering the period of June and July of 2017. In this period, we analyzed how the brand develops its communication, mapping the characteristics and their differences on Instagram. The communication strategy most used by the brand Adidas Brasil and Adidas Originals was identified, as well as the brand operates in each profile. It was analyzed in which phase of the digital presence each profile is acting (STRUTZEL, 2015) and finalizing, it is presented which social media generates more engagement for the brand, through a qualitative/quantitative research, using the content analysis. Adidas Brasil and Adidas Originals use testimonial and information strategies through their publications on Instagram profiles. This work concludes that the two profiles are not at all stages of the digital presence, but Adidas Originals is the one that generates more engagement with the public.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.336
Teacher spread0.302 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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