Reasons, Rewards, Regrets: Privacy Considerations in Location Sharing as an Interactive Practice
Bibliographic record
Abstract
Rapid growth in the usage of location-aware mobile phones has enabled mainstream adoption of location-sharing services (LSS). Integration with social-networking services (SNS) has further accelerated this trend. To uncover how these developments have shaped the evolution of LSS usage, we conducted an online study (N = 362) aimed at understanding the preferences and practices of LSS users in the US. We found that the main motivations for location sharing were to connect and coordinate with one's social and professional circles, to project an interesting image of oneself, and to receive rewards offered for 'checking in.' Respondents overwhelmingly preferred sharing location only upon explicit action. More than a quarter of the respondents recalled at least one instance of regret over revealing their location. Our findings suggest that privacy considerations in LSS are affected due to integration within SNS platforms and by transformation of location sharing into an interactive practice that is no longer limited only to finding people based on their whereabouts. We offer design suggestions, such as delayed disclosure and conflict detection, to enhance privacy-management capabilities of LSS. Copyright is held by the author/owner.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".