  Privacy policies are legal documents that describe how a website will
collect, use, and distribute a user's data. Unfortunately, such documents are
often overly complicated and filled with legal jargon; making it difficult for
users to fully grasp what exactly is being collected and why. Our solution to
this problem is to provide users with a coverage analysis of a given website's
privacy policy using a wide range of classical machine learning and deep
learning techniques. Given a website's privacy policy, the classifier
identifies the associated data practice for each logical segment. These data
practices/labels are taken directly from the OPP-115 corpus. For example, the
data practice "Data Retention" refers to how long a website stores a user's
information. The coverage analysis allows users to determine how many of the
ten possible data practices are covered, along with identifying the sections
that correspond to the data practices of particular interest.
