  We provide a simple but novel supervised weighting scheme for adjusting term
frequency in tf-idf for sentiment analysis and text classification. We compare
our method to baseline weighting schemes and find that it outperforms them on
multiple benchmarks. The method is robust and works well on both snippets and
longer documents.
