Understanding and capturing people’s privacy policies in a mobile social networking application

  title={Understanding and capturing people’s privacy policies in a mobile social networking application},
  author={Norman M. Sadeh and Jason I. Hong and Lorrie Faith Cranor and Ian Fette and Patrick Gage Kelley and Madhu K. Prabaker and Jinghai Rao},
  journal={Personal and Ubiquitous Computing},
A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends, family, and… CONTINUE READING
Highly Influential
This paper has highly influenced 18 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 368 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 203 extracted citations

Learning Privacy Preferences

2011 Sixth International Conference on Availability, Reliability and Security • 2011
View 4 Excerpts
Highly Influenced

Deriving Privacy Settings for Location Sharing: Are Context Factors Always the Best Choice?

2018 IEEE Symposium on Privacy-Aware Computing (PAC) • 2018
View 3 Excerpts
Highly Influenced

Improved Recommender for Location Privacy Preferences

Computer and Information Science • 2015
View 3 Excerpts
Highly Influenced

369 Citations

Citations per Year
Semantic Scholar estimates that this publication has 369 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 31 references

Similar Papers

Loading similar papers…