I hate ads but not the advertised brands: a qualitative study on Internet users' lived experiences with YouTube ads
Bibliographic record
Abstract
Purpose This paper aims to explore Internet users' lived experiences with video ads, both skippable and nonskippable, while watching content on YouTube. Design/methodology/approach In-depth interviews were conducted with 22 participants. Findings The participants unanimously expressed dissatisfaction with YouTube ads. The dissatisfaction was directed to the platform but did not spill over to the advertised brand/product. Ethical concerns related to privacy also emerged. Specifically, with respect to nonskippable ads, the participants expressed dislike for forced viewing and explained how they would engage in extraneous activities during the ads. Nonetheless, they appreciated the flexibility offered by skippable ads. They also elaborated on how, why and when they would skip/not skip skippable ads. Originality/value The findings are discussed in light of the literature on not only online advertising but also platform switching versus continuance intention, spillover effect, privacy–personalization paradox and visual attention.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".