A Cross-Cultural Comparison of Character Presence in Advergames and Its Impact on Brand Outcomes
Bibliographic record
Abstract
This study aims to investigate the cross-cultural impact of character presence in advertising games on brand outcomes. The study was quantitative in nature and selected 500 participants through snow-ball sampling technique. The participants were Saudis and Malaysians. A questionnaire was created to collect data from the survey sample. The data collected was then analyzed using the Social Sciences Statistics Package version 23.0 (SPSS). Descriptive statistical analysis using standard deviation, mean, and frequencies were applied. Pearson Correlation was applied to identify the relation among the variables.The study found no significant correlation between brand outcome and character presence in advergaming where a significant correlation was found in culture and character presence in advergames.The study concluded that humanoid characters in advergames should be operated attentively because interesting or engaging game charcaters affect the player’s attitude in a different way depending upon the classification of the brand and its target market’s ethnic traditions and history.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".