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.
@article{arxiv.1604.04810,
title = {Participation Cost Estimation: Private Versus Non-Private Study},
author = {Joshua Joy and Sayali Rajwade and Mario Gerla},
journal= {arXiv preprint arXiv:1604.04810},
year = {2016}
}