22RanText & sentiment

Omicron variant tweets

The same pipeline as project 20, run on 17,046 tweets about the Omicron variant. I dropped incomplete rows, cleaned the text, drew word clouds and summed the VADER scores.

Original tutorial by Aman Kharwal: Omicron Variant Sentiment Analysis (opens in a new tab)

What it printed in 2022

Numbers read from the saved notebook outputs. Cell numbers count every cell in the notebook, Markdown included, starting at 1.
Output	Value	Cell #
Overall verdict	Neutral	15

Cell # counts every cell from the top of the notebook, Markdown included, starting at 1.

The notebook printed only the verdict, not the sums behind it.

The data

A Kaggle tweet collection bundled as omicron.csv in the repository.

Tweets with user names and profiles. No tweet text or user detail is shown here.

What I'd do differently

Plot sentiment over time. The interesting question is how the mood moved as the variant spread.
Keep rows with missing profile fields.