Understanding User Privacy Perceptions in Video Conferencing: Insights from a Feature-Specific User Study
Bibliographic record
Abstract
The widespread adoption of video conferencing platforms has raised privacy concerns. Recent studies have shown that users express various concerns, such as reluctance toward mandatory camera-on policies, but these findings remain coarse-grained, lacking details on specific features and social relationships. This paper investigates how users perceive privacy with respect to various features in video conferencing platforms. Using the framework of contextual integrity, we analyze information flows across diverse scenarios, such as business meetings and online classes. Our findings reveal nuanced privacy perceptions regarding features that have been discontinued (e.g., attention tracking) or adjusted (e.g., meeting recording), suggesting that the handling of these features could have aligned better with users’ privacy expectations. Additionally, we identify emerging privacy concerns about the pinning and spotlighting features, as users often feel great discomfort when their video is pinned or spotlighted by others in specific contexts. These insights provide a deeper understanding of privacy in video conferencing, highlighting the need for more refined privacy controls and a proactive approach to feature development.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".