My project basically on find best sentiment results on specific topic in twitter using python
sentiments are positive,negative and neatral
step for doing in project.
1] To enter keywords and find tweets basis on that and second thing is to create dictionary and collect words for which topic search for tweet.
2] to create csv file of collected tweets and their original sentiments.
3] to use two different classifier Naive Bayes and RNN and store results seperately.
4] main thing is when to find out features of tweets so to check any tweets contains words from dictionary. if contain so find out features of that tweets using priority to that words.
ex. if my tweet is line of length is good.. in this line word is in my dictionary so find out features according to that words ad give priority for that sentence is positive negative or neatral.
5] show the output in piechart for two different classifier.
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