Listen "Shadow Profiles on Social Networks"
Episode Synopsis
Emre Sarigol joins me this week to discuss his paper Online Privacy as a Collective Phenomenon. This paper studies data collected from social networks and how the sharing behaviors of individuals can unintentionally reveal private information about other people, including those that have not even joined the social network! For the specific test discussed, the researchers were able to accurately predict the sexual orientation of individuals, even when this information was withheld during the training of their algorithm. The research produces a surprisingly accurate predictor of this private piece of information, and was constructed only with publically available data from myspace.com found on archive.org. As Emre points out, this is a small shadow of the potential information available to modern social networks. For example, users that install the Facebook app on their mobile phones are (perhaps unknowningly) sharing all their phone contacts. Should a social network like Facebook choose to do so, this information could be aggregated to assemble "shadow profiles" containing rich data on users who may not even have an account.
More episodes of the podcast Data Skeptic
Video Recommendations in Industry
26/12/2025
Eye Tracking in Recommender Systems
18/12/2025
Cracking the Cold Start Problem
08/12/2025
Shilling Attacks on Recommender Systems
05/11/2025
Music Playlist Recommendations
29/10/2025
Bypassing the Popularity Bias
15/10/2025
Sustainable Recommender Systems for Tourism
09/10/2025
Interpretable Real Estate Recommendations
22/09/2025
ZARZA We are Zarza, the prestigious firm behind major projects in information technology.