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Record W2051633659 · doi:10.2501/s002184990808032x

The Impact of SMS Advertising on Members of a Virtual Community

2008· article· en· W2051633659 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

VenueJournal of Advertising Research · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCredibilityShort Message ServiceAdvertisingSource credibilityService (business)Computer sciencePsychologyInternet privacyBusinessMarketingPolitical scienceTelecommunications

Abstract

fetched live from OpenAlex

<h3>ABSTRACT</h3> This empirical research brings interesting insights concerning mobile commerce. Our objective is to determine the influence of language (conventional language versus short message service (SMS) language) and spokeperson on the effectiveness of SMS advertising. The experiment took place in a virtual community of gamers equipped with cellular telephones. After having exchanged messages during several days in the forum9s community, participants received one of four messages (varied with the language and the source of the message) that they evaluated afterward. Our results offer new and significant insights to managers wishing to use this medium. Unlike what is often thought, our results show that SMS language is not always recommended. While known and credible companies could use shortened, original, and entertaining SMS language, little known companies or ordinary spokepersons should refrain from doing so. Thus a message relayed by a spokeperson with little credibility, even if he is a member of the targeted community, should have a sober and clear content with a conventional language.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.155
GPT teacher head0.464
Teacher spread0.310 · 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