nlp_sent.py

import re
from textblob import TextBlob


class nlp():
    def clean_tweet(self, tweet):
        '''
        Utility function to clean tweet text by removing links, special characters
        using simple regex statements.
        '''
        return ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)", " ", tweet).split())
 
    def get_tweet_sentiment(self, tweet):
        '''
        Utility function to classify sentiment of passed tweet
        using textblob's sentiment method
        '''
        # create TextBlob object of passed tweet text
        analysis = TextBlob(self.clean_tweet(tweet))
        # set sentiment
        return analysis.sentiment.polarity
        """if analysis.sentiment.polarity > 0:
                                    return 'positive'
                                elif analysis.sentiment.polarity == 0:
                                    return 'neutral'
                                else:
                                    return 'negative'"""