Sentiment analysis

Movie reviews

Based on Tutorial on Python Spot site. The original tutorial handles features incorrectly (as letters instead of words) but I corrected it.

In Natural Language Processing, you can perform Sentiment Analysis such as to classify text into categories like positive, neutral or negative.

This requires NLTK to be installed.

$ pip install nltk

• classify.py

    """
    Classifier application.
  
    Sentiment Analysis demo.
    """
    from nltk.classify import NaiveBayesClassifier
  
  
    VOCAB = {
        "positive": [
            "awesome",
            "outstanding",
            "fantastic",
            "terrific",
            "good",
            "nice",
            "great",
            ":)",
        ],
        "negative": ["bad", "terrible", "useless", "hate", ":("],
        "neutral": [
            "movie",
            "the",
            "sound",
            "was",
            "is",
            "actors",
            "did",
            "know",
            "words",
            "not",
        ],
    }
  
  
    def feats(words):
        return {word: True for word in words}
  
  
    def train(vocab):
        positive_features = [feats(vocab["positive"]), "pos"]
        negative_features = [feats(vocab["negative"]), "neg"]
        neutral_features = [feats(vocab["neutral"]), "neu"]
  
        train_set = [positive_features, negative_features, neutral_features]
  
        return NaiveBayesClassifier.train(train_set)
  
  
    def classify(classifier, words):
        count_pos = 0
        count_neg = 0
  
        for word in words:
            result = classifier.classify(feats(word))
  
            if result == "pos":
                count_pos += 1
            elif result == "neg":
                count_neg += 1
  
        score_pos = count_pos / len(words)
        score_neg = count_neg / len(words)
  
        return score_pos, score_neg
  
  
    def main(sentence):
        classifier = train(VOCAB)
  
        sentence = sentence.lower()
        # Or use a tokenizer.
        words = sentence.split(" ")
  
        score_pos, score_neg = classify(classifier, words)
  
        print(f"Positive: {score_pos}")
        print(f"Negative: {score_neg}")
  
  
    if __name__ == "__main__":
        main("Awesome movie, I liked it")
  

Example use:

$ python classify.py

Positive: 1.0
Negative: 0.0