Nowhere to hide: Exploring user-verification across Flickr accounts

This work presents improved audio-based user-verification analysis and results on Flickr videos, using a subset of the MediaEval 2011 [1] data set. User-verification is a new task, where the goal is to determine if two pieces of media are uploaded by the same user. Our best results, with a 19.7% Equal Error Rate, and a 53.9% Miss Rate at 1% False Positive, are obtained using an i-vector [2] system. A frequency-matching system that requires 96% less computation time than the other systems is also explored, and may be better suited for processing large datasets from Flickr and other social networks. The results have significant privacy implications as they present a framework for exploiting users´ tendencies to assume that different accounts remain as separate realms.