title: Converting Sentiment Probabilities to a Score
body: <p>I have run text through a sentiment analysis model, and it gives me 3 probabilities for if the text is Negative, Neutral or Positive e.g.</p>
  <pre><code>[Negative = 0.38]
  [Neutral = 0.42]
  [Positive = 0.20]
  </code></pre>
  <p>I am wanting to convert this to a score so that each text string has a score with higher scores meaning the text is more positive. I was thinking of just doing [Positive - Negative] and ignoring the neutral case to generate a score, but wondered if there were any better ideas as this seems overly simple.
  I want to generate a score so I can run regressions on these scores for predictive purposes.</p>
  <p>Doing that sum on my dataset gets me a distribution that looks like this: <a href="https://i.imgur.com/DewzBRM.jpeg" rel="nofollow noreferrer">https://i.imgur.com/DewzBRM.jpeg</a>
  (Sorry for not embedding, I don't have the 'reputation' required to do so).</p>
  <p>This seems pretty decent, but I was curious if anyone had other alternative ideas.</p>
  <p>Thanks in advance</p>