Participation Cost Estimation: Private Versus Non-Private Study
This addresses user privacy concerns in location-based services, but appears incremental as it builds on existing privacy mechanisms.
The study tackled the problem of estimating real-time crowd levels at points of interest by comparing user participation costs in private versus non-private data sharing, showing that privacy-preserving mechanisms can incentivize participation in private studies.
In our study, we seek to learn the real-time crowd levels at popular points of interests based on users continually sharing their location data. We evaluate the benefits of users sharing their location data privately and non-privately, and show that suitable privacy-preserving mechanisms provide incentives for user participation in a private study as compared to a non-private study.