How can you use VADER sentiment analysis in NLTK to filter training data for text generators

Question

With the help of Python programming, can you use VADER sentiment analysis in NLTK to filter training data for text generators?

Answer 1

To use VADER sentiment analysis in NLTK to filter training data for text generators, you can compute sentiment scores for each text and filter based on positive, neutral, or negative sentiment thresholds. Here is the code reference you can refer to:

In the above code, we are using steps like:

• Sentiment Analysis:
  • Compound score in VADER determines overall sentiment:
    • Positive: compound > 0.5
    • Negative: compound < -0.5
• Filtering:
  • Separate texts into positive and negative categories based on thresholds.
• Result: Filtered data can be used to train sentiment-specific text generators.

The output of the above code would be :

Hence, by referring to the above, you can use VADER sentiment analysis in NLTK to filter training data for text generators.

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