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Sentiment analysis provides us a small glimpse of the meaning of texts with a rather directly interpretable method. While it has its limitations, it's a good place to begin working with textual data. There's a number of out-of-the-box tools in Python we can use for sentiment analysis.

ds_tweets with the datetime index has been loaded for you.

Cet exercice fait partie du cours

Analyzing Social Media Data in Python

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Instructions

  • Load SentimentIntensityAnalyzer from nltk.sentiment.vader.
  • Instantiate a new SentimentIntensityAnalyzer object.
  • Generate sentiment scores with the .apply() method and the analyzer's polarity_scores() function.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Load SentimentIntensityAnalyzer
____

# Instantiate new SentimentIntensityAnalyzer
sid = ____

# Generate sentiment scores
sentiment_scores = ds_tweets['text'].____(____)
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