  Advertising, long the financial mainstay of the web ecosystem, has become
nearly ubiquitous in the world of mobile apps. While ad targeting on the web is
fairly well understood, mobile ad targeting is much less studied. In this
paper, we use empirical methods to collect a database of over 225,000 ads on 32
simulated devices hosting one of three distinct user profiles. We then analyze
how the ads are targeted by correlating ads to potential targeting profiles
using Bayes' rule and Pearson's chi squared test. This enables us to measure
the prevalence of different forms of targeting. We find that nearly all ads
show the effects of application- and time-based targeting, while we are able to
identify location-based targeting in 43% of the ads and user-based targeting in
39%.
