Step 12: Sentiment Score Calculation

You can calculate a sentiment score for each review using a sentiment analysis tool like TextBlob or Vader. This can provide a more quantitative measure of the sentiment expressed in the reviews.

from textblob import TextBlob
# Define a function to calculate sentiment
def calculate_sentiment(text):
    return TextBlob(text).sentiment.polarity
# Apply the function to the review_body_clean column
df['sentiment_score'] = df['review_body_clean'].apply(calculate_sentiment)
# Print the average sentiment score
print(df['sentiment_score'].mean())

Please note that you’ll need to install the nltk and textblob libraries to run this code, which you can do using pip:

pip install nltk textblob

Let me know if you’d like to proceed with any of these steps, or if there’s something else you’d like to do.

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