Get the positive and negative words from a Textblob based on its polarity in Python (Sentimental analysis)

Question

I have a text blob in which i am classifying the text as positive if polarity is > 0, neutral if = 0, and negative if < 0. How can i get the words based on which it is classifying as positive, negative or neutral?

Answer 1

I hope the following code will help you:

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

text          = "I feel the product is so good" 

sent          = TextBlob(text)
# The polarity score is a float within the range [-1.0, 1.0]
# where negative value indicates negative text and positive
# value indicates that the given text is positive.
polarity      = sent.sentiment.polarity
# The subjectivity is a float within the range [0.0, 1.0] where
# 0.0 is very objective and 1.0 is very subjective.
subjectivity  = sent.sentiment.subjectivity

sent          = TextBlob(text, analyzer = NaiveBayesAnalyzer())
classification= sent.sentiment.classification
positive      = sent.sentiment.p_pos
negative      = sent.sentiment.p_neg

print(polarity,subjectivity,classification,positive,negative)