This program trains machine learning models for applying them to the analysis of tweets related with an specific user query Note that the code is provisionally not commented After much testing, the average acuracy is 73.5%
1º step: run trainmodel3.py to generate clasifier0.pickle and clasifier1.pickle.
2º step: run mainprogram.py to automaticcally analize the proportion of positive and negative tweets containing a given query.