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This project aims at extracting tweets that include the topic ‘Taylor Swift’ and performing a detailed analysis by exploiting natural language processing.

1. Data Collection:

  • Install Twint library for Python to scrape tweets with the keyword "Taylor Swift."

  • Use Twint to scrape tweets and store them in a CSV file.

2. Data Preprocessing:

 • Handle null values by dropping unnecessary columns and rows.

  • Identify the primary key for the dataset.

  • Preprocess tweet text by removing hashtags, URLs, mentions, emojis, punctuation, and digits.

 • Tokenize the cleaned tweets and remove stop words.

3. Save the cleaned data in a CSV file.

4. Set up HarperDB:

  • Create a HarperDB account and instance.

  • Launch the instance, create a schema, and define tables.

  • Import the cleaned data into HarperDB.

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See part two of this series as well.

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