1. Read the following:
- Ball – 2018 – ‘News’ spreads faster and more widely when it’s false
- Fenkel – 2021 – The Most Influential Spreader of Coronavirus Misinformation Online
- Hayes – 2013 – In Data We Trust
- Kaplan et al. – 2021 – Is Confirmation Bias Guiding COVID Vaccine Recommendations?
- Open Data Handbook – Why Open Data?
2. Take the quiz due before next class start.
3. Download Tableau and do extra credit.
4. Look over in-class work for week ahead (see schedule).
Bonus reads…
An old but still relevant TED talk by Eli Pariser on how the web is being inconspicuously personalized for individual tastes creating bubbles of like-minded people.…and its critique…and a more recent take on the topic.
In addition…
We will discuss open data sets this week. Aside from what’s in readings and the class materials here are some others:
- Business: data.gov’s “Impact” section
- Science: The Genomes Unzipped project
- Government: New York City parking violations
- Journalism: ProPublica data sets
- Random: Tableau public visualizations (often based on open data)
- More Random: Reddit’s Data Is Beautiful (usually has source data for the visualizations linked)
In addition take 2…
We will be talking about visualizations that are scheduled for Week 4. The idea here is to work ahead a bit so the following week is spent on Tableau hands on (in class and assignment 1) the entire session.
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