This is not an expert answer but from a grad student
1. $ easy_install twitter
import twitter
twitter_search = twitter.Twitter(domain="T
Then you can explore i guess..
2. They are 2 approaches for sentiment analysis. (a) Machine learning based: Use it when you have a domain specific problem. NLTK has many examples and functions for learning based analysis. (b) Lexicon based: Use it when you want a generic solution but ready for more error. For lexicon approach use NLTK combined with sentiwordnet. The steps are: tokenize words, lematize them (gud -> good), POS tag, pick the adjectives and assign rating to them. Take care of negators (not good) and intensifiers (very good). The rating may be binary (positve, negative) or real value (stars). With this you can expect a reasonable accuracy.
3. You can plug the developed python+NLTK code into Django project. Use HTML5 for GUI and use python to process the request
4. For training, yes. For the final implementation, no.
5. Python + NLTK
Read full article from (11) What steps should I take to create a sentiment analysis web application using Twitter? - Quora
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