Machine Learning - Sentiment Analysis

import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer

# Download VADER lexicon (if not already downloaded)
nltk.download('vader_lexicon')

# Initialize the sentiment analyzer
sid = SentimentIntensityAnalyzer()

def analyze_sentiment(text):
    # Calculate sentiment scores
    sentiment_scores = sid.polarity_scores(text)

    # Determine sentiment label based on the compound score
    compound_score = sentiment_scores['compound']
    if compound_score >= 0.05:
        return "Positive"
    elif compound_score <= -0.05:
        return "Negative"
    else:
        return "Neutral"

# Input text for analysis
text = "I love this product! It's amazing."

# Perform sentiment analysis
sentiment = analyze_sentiment(text)

# Display the sentiment result
print(f"Sentiment: {sentiment}")