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Comparative Sentiment Evaluation of 1000 Tweets: Biden vs. Trump

On this sentiment evaluation undertaking, we carried out a comparative examine on 1000 tweets associated to present President Joe Biden and former President Donald Trump. My goal was to realize insights into the emotions expressed by Twitter customers relating to these two political figures. I utilized Python for scraping the tweets and employed the NRC lexicon to find out the sentiment classes related to every tweet. And visualized the output utilizing Tableau Desktop.

Methodology: To conduct the sentiment evaluation, we employed Python’s knowledge scraping bundle known as snscrape to gather 1000 tweets on every key phrase. I then utilized the NRC lexicon, a widely-used useful resource for sentiment evaluation, to categorize every tweet into predefined sentiment classes. The NRC lexicon consists of a complete checklist of phrases related to particular sentiments.

I cant say what are the exact insights right here as a result of the dataset was too small and the strategy itself has flaws. However nonetheless I consider it’s nonetheless attention-grabbing and determined to share it right here with you.

Comments ( 5 )

  1. Good job. Could be worth thinking about what demographics are more likely to use Twitter, and how this may have affected your output.

  2. The fact trust is so high for either is why were screwed

  3. Biden and trump are switched from row 1 to 2

  4. Why is the bottom flipped compared to the top?

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