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Record W2122351239 · doi:10.1123/ijsc.2.4.466

Online and Off-Line Advertising During March Madness: Which Companies Drive Consumers to the Web?

2009· article· en· W2122351239 on OpenAlexaff
Ann Pegoraro, Norm O’Reilly, Martin Giguere

Bibliographic record

VenueInternational Journal of Sport Communication · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsLaurentian University
Fundersnot available
KeywordsAdvertisingWebcastOnline advertisingBasketballBusinessAction (physics)Duration (music)Search advertisingContextual advertisingOnline videoThe InternetMultimediaComputer scienceWorld Wide WebHistoryArt

Abstract

fetched live from OpenAlex

This study examined the advertisement structure of online and off-line broadcasts as consumer drivers to Web sites through the integration of specific calls to action. Content analysis was performed on ads aired during the online and off-line broadcasts of an NCAA Men’s Basketball Tournament. The key finding of this research is that communication and technology companies value advertising during online sporting-event broadcasts, because these companies were significantly more visible during the online broadcasts than the television broadcasts (χ 2 = 6.67, p = .017). A much higher percentage of online ads were shorter (15 seconds) in duration (χ 2 = 7.029, p = .01), appealed to fantasy (χ 2 = 8.494, p = .004), and used advertising execution techniques emphasizing new products or features (49%) more often than in television ads (18%; χ 2 = 11.078, p = .001). The findings provide insight into how calls to action in advertisements during Webcasts and traditional television offerings can move consumers to Web sites.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.672
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.025
GPT teacher head0.293
Teacher spread0.268 · 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 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".

Quick stats

Citations3
Published2009
Admission routes1
Has abstractyes

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