title: How to tune sentiment analysis when one algorithm says positive and one negative?
body: <p>I'm currently working on a project and I use [Google CNL] <a href="https://cloud.google.com/natural-language" rel="nofollow noreferrer">1</a> and [PyFeel] <a href="https://github.com/AdilZouitine/pyFeel" rel="nofollow noreferrer">2</a> to perform a sentiment analysis of a dataset.</p>
  <p>I have read a lot of articles and tips on how to tune the classifier, but I'm more looking for some ideas on: what to do when technology 1 says positive and technology 2 says negative?</p>
  <p>What can I do in this situation?</p>