title: Good algorithm for sentiment analysis
body: <p>I tried naive bayes classifier and it's working very bad. SVM works a little better but still horrible. Most of the papers which i read about SVM and naive bayes with some variations(n-gram, POS etc) but all of them gives results close to 50% (authors of articles talk about 80% and high but i cannt to get same accurate on real data). </p>
  
  <p>Is there any more powerfull methods except lexixal analys? SVM and Bayes suppose that words independet. These approach called "bag of words". What if we suppose that words are associated? </p>
  
  <p>For example: Use apriory algorithm to detect that if sentences contains "bad and horrible" then 70% probality that sentence is negative. Also we can use distance between words and so on.</p>
  
  <p>Is it good idea or i'm inventing bicycle? </p>