Privacy in Location-Sharing Social Media

Why people are concerned about sharing their location

In this research we investigate what causes people to be concerned about sharing their location with their peers. We found that people are concerned about preserving their relationship boundaries in online communication. If they are afraid that the technology will change their relationship with people, privacy concerns ensue. We additionally found that lying as a strategy to preserve these relationship boundaries backfires: it actually increases people's privacy concerns.

This part of the project is lead by Xinru Page. I am an advisor on statistical modeling.

Understanding and influencing users' decision to share their location

As a side project, I looked in more detail at users' decision to share - or not share - their location with others. Specifically, we considered the number of sharing options leads to the most sharing. Recent privacy research has claimed that more options are better, because otherwise users will "err on the safe side" and disclose less. In line with decision making literature and the notion of "privacy calculus", our results indicate that users instead employ a compensatory decision strategy, switching to more sharing or less sharing depending on the subjective distance between the omitted option(s) and the remaining options.

Finally, I worked on reducing the complexity of location-sharing decisions by giving users recommendations. I demonstrated that such recommendations can also have a persuasive effect, and that they can create an optimal balance between user empowerment and usability.


Xie, J., Knijnenburg, B.P., Jin, H.: Location Sharing Privacy Preference: Analysis and Personalized Recommendation. Full paper at the International Conference on Intelligent User Interfaces (IUI) 2014, DOI: 10.1145/2557500.2557504, download here.

Acceptance rate: 24%.

Knijnenburg, B.P.: The Persuasive Effect of Privacy Recommendations for Location Sharing Services. Full paper at the 12th Annual Pre-ICIS Workshop on HCI Research in MIS (SigHCI) 2013, download here.

Won best paper award among 12 accepted papers.

Chow, R., Jin, H., Knijnenburg, B.P., Saldamli, G.: Differential data analysis for recommender systems. Short paper at the ACM Conference on Recommender Systems (RecSys) 2013, DOI: 10.1145/2507157.2507190, download here.

Page, X., Knijnenburg, B.P., Kobsa, A.: FYI: Communication Style Preferences Underlie Differences in Location-Sharing Adoption and Usage. Full paper at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) 2013, DOI: 10.1145/2493432.2493487, download here.

First-round acceptance rate: 18%; awarded with an honorable mention.

Knijnenburg, B.P., Kobsa, A., Jin, H.: Preference-based Location Sharing: Are More Privacy Options Really Better? Full paper at the ACM SIGCHI Conference on Human factors in computing systems (CHI) 2013, DOI: 10.1145/2470654.2481369, download here.

Acceptance rate: 23%.

Page, X., Knijnenburg, B.P., Kobsa, A.: What a Tangled Web We Weave: Lying Backfires in Location-Sharing Social Media. Full paper at the ACM Conference on Computer Supported Cooperative Work (CSCW) 2013, DOI: 10.1145/2441776.2441808, download here.

Acceptance rate: 36%.

Jin, H., Saldamli, G., Chow, R., Knijnenburg, B.P.: Recommendations-based Location Privacy Control. Short paper at the IEEE Pervasive Computing and Communication conference (PerCom) 2013, download here.

Saldamli, G., Chow, R., Jin, H., Knijnenburg, B.P.: Private proximity testing with an untrusted server. Full paper at the ACM conference on Security and privacy in wireless and mobile networks (WiSec) 2013, DOI: 10.1145/2462096.2462115.

Acceptance rate: 37%.

Page, X., Kobsa, A., Knijnenburg, B.P.: Don't Disturb My Circles! Boundary Preservation is at the Center of Location-Sharing Concerns. Full paper accepted for oral presentation at the International AAAI Conference on Weblogs and Social Media (ICWSM) 2012, download here.

Acceptance rate: 9%.