Analyzing the sentiment of a sentence

Sentiment analysis refers to procedures of finding whether a specified part of text is positive, negative, or neutral. This technique is frequently considered to find out how people think about a particular situation. It evaluates the sentiments of consumers in different forms, such as advertising campaigns, social media, and e-commerce customers.

How to do it...

1. Create a new file and import the chosen packages:

import nltk.classify.util
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import movie_reviews

2. Describe a function to extract features:

def collect_features(word_list):
  word = []
  return dict ([(word, True) for word in word_list])

3. Adopt movie reviews in NLTK as training data:

if __name__=='__main__':
  plus_filenum = movie_reviews.fileids('pos')
  minus_filenum = movie_reviews.fileids('neg')

4. Divide the data into positive and negative reviews:

  feature_pluspts = [(collect_features(movie_reviews.words(fileids=[f])),
'Positive') for f...