More Ads, More Viewers? Analyzing Behavioral Shifts from Advertising Permissions to Live Streaming Consumption
Bibliographic record
Abstract
There has been little exploration of how audience content consumption may change in response to advertising permissions on live streaming platforms. Brands use ads to generate revenue through ad exposure, but is this benefit thwarted by the reduction of audience consumption of content? Using a dataset containing over 12 million observations in the live streaming space and a difference-in-differences estimation approach, the authors study the effects of a policy intervention by a live streaming platform that provided (some) streamers the ability to display midroll advertisements. Although the ad avoidance literature infers that audiences view ad-supported content unfavorably, the results of this study indicate that providing the mere ability to introduce midroll advertisements has a notable positive effect on live streaming content consumption (average viewership and total hours watched). The authors discover that a viable explanation for this response is through increases in broadcasting airtime, stream frequency (somewhat), and quality by streamers after the intervention, as these adjustments are drastically easier to implement in a live streaming setting than in more traditional forms of media. The authors further explore heterogeneity in these effects in relation to initial streamer success, streaming tenure, content activity, culture (of the streamer and audience), and impact across time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".