CS3 Case Study

This repository contains the study, deliverable, data, and reference materials necessary to complete the COVID-19 Twitter Reactions Case Study

In this project, you will take on the role of a public health data analyst during the early days of the COVID-19 pandemic. Your mission is to explore how public sentiment varied depending on what people were tweeting about.

Dataset Information

File to use:
data/df_us_sentiment.csv

This dataset includes:

• OriginalTweet: The text of the tweet
• Location: General region where tweet originated
• TweetAt: The date of the tweet
• Sentiment: Pre-labeled as Positive, Negative, or Neutral
• VADER Score: Numeric sentiment score from -1 (very negative) to +1 (very positive)

Note: I have also included the original dataset, but that won't be needed for this project.

How to Get Started

• Read through the (CS3 Hook Document.pdf)
• Follow the case study rubric (CS3 Rubric.pdf) to structure your project
• Check out the reference articles. They will help you understand:
  • Why tracking public sentiment during COVID-19 matters
  • How sentiment analysis methods like VADER work
• Open a new Jupyter notebook (your_notebook.ipynb)
• Load the dataset (df_us_sentiment.csv)
• Choose your keywords carefully