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Record W2607302408 · doi:10.1002/mar.20999

Consumer Branded #Hashtag Engagement: Can Creativity in TV Advertising Influence Hashtag Engagement?

2017· article· en· W2607302408 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychology and Marketing · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsAdvertisingCreativityNoveltyContext (archaeology)PsychologyRelevance (law)Social mediaBusinessComputer scienceSocial psychologyWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT This study examines the effects of creativity on consumer branded hashtag engagement in the context of TV advertising. Applying a qualitative design, two types of TV commercials were selected: humorous and warmth. This was followed by a quantitative study with 259 participants suggesting that novelty and relevance in TV advertisements together with brand familiarity are important drivers of consumer branded hashtag engagement. Consumer branded hashtag engagement, in turn, encourages consumers to share advertisements online through different social media platforms. In addition, brand familiarity and the type of TV advertisement were found to be significant moderators. The results of this study highlight the pertinence of hashtags for consumer–brand engagement, and contribute to a better understanding of consumer branded hashtag engagement in advertising. Guidance to advertisers on how to utilize creativity in TV advertisements to encourage consumer engagement with the brand is offered.

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.

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)0.010
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.381
Teacher spread0.337 · 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