sentiment.py

from textblob import TextBlob
import nltk
nltk.download('movie_reviews')
nltk.download('punkt')

'''
    Note that a key weakness of TextBlob is that it was trained on IMDB movie reviews, and will not pick up on everything a human would. 
'''

''' returns the sentiment of provided text '''
def get_sentiment_of_text(text='UCF drivers are terrible.'):
    text_blob = TextBlob(text)
    
    # polarity is a score ranging from -1.0 to 1.0, where -1 is extremely negative and 1.0 is extremely positive
    polarity = text_blob.sentiment.polarity

    return polarity


# driver code
if __name__ == '__main__':
    my_text = 'UCF drivers are terrible.'
    sentiment = get_sentiment_of_text(my_text)
    print('Text: ' + my_text)
    print('Sentiment score: ' + str(sentiment))