ASAP

This project would help us to visualize sentiment analysis of Tweets about COVID-19.

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Inspiration

Exploring the emotional changes during the COVID-19 pandemic would be helpful during this period.

What it does

This project would visualize people's emotions in three categories, positive, negative, and neutral.

How we built it

Used an existing GitHub repo for the corpus, and used NLTK for analysis.

Challenges we ran into

  1. How to get the most recent tweets.
  2. How to get the emotional change of a user.

Accomplishments that we're proud of

We successfully visualize the data.

What we learned

  1. NLTK
  2. Text processing by removing punctuation, stopwords, etc.

What's next for ASAP

We want to build an instantaneous emotional track system. Maybe track the emotion of every user as well.

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