  Confidential text corpora exist in many forms, but do not allow arbitrary
sharing. We explore how to use such private corpora using privacy preserving
text analytics. We construct typical text processing applications using
appropriate privacy preservation techniques (including homomorphic encryption,
Rademacher operators and secure computation). We set out the preliminary
materials from Rademacher operators for binary classifiers, and then construct
basic text processing approaches to match those binary classifiers.
