1) Read these Lost Stories stories:
2) Choose 2-3 of these stories, and in the comments, leave some thoughts on what you think works and what questions you have about the stories — the focus, approach, the voice, etc. Think about our conversation about the fire-behind-football-game story.
3) Look over the Birmingham News photos in Dropbox. (Captions are in a Word doc at the bottom of the page.) Come to class Tuesday with your top three. In the meantime, if you feel strongly about one (or more) of these, email me and let me know why.
4) Look over the schedule for the Lost Stories project and let me know if you have any questions about the deadlines. We will talk to Elizabeth at AMG next week about the engagement/distribution plan.
Read Fire Raged, They Played On, and the Photo Still Beguiles (in the NYT) and keep a list in a Google Doc of everything the reporter, Sarah Lyall, had to report in order to tell the story behind the photo. Before the start of class, share your Google Doc with me.
In the comments, leave some thoughts on what you think works and what questions you have about the stories — the focus, approach, the voice, etc.
1) Bookmark jn430.ua.edu. This is where I will post all of your assignments and where we will work collaboratively to discuss reading and projects.
2) Please answer this short questionnaire. Thanks!
Here is the landline survey. Share away.
1) Read Clara Guibourg’s 4 Mistakes in Data Journalism and How to Avoid Them and review Become Data Literate in 3 Simple Steps from the Data Journalism Handbook.
2) For your quiz, Make a copy of the spreadsheet of responses from the spring break survey we made and distributed. Using formulas in the spreadsheet itself or Fusion Tables, answer these questions for your third quiz. The quiz must be completed by 11:59 p.m. on Monday, March 28, 2016.
Over the break, please read Kathryn Schulz’ The Really Big One (sorry, people headed to the West Coast). It’s a great piece of journalism, full stop, but it’s also a great example of how data can fuel great storytelling. (That’s three uses of “great” in one sentence if you’re keeping count.) Also, read Oliver Roeder’s A Plagiarism Scandal is Unfolding in the Crossword World. It’s a great example of data-analysis-as-reporting.
We’ll talk about these when we get back to class on 3/22. We’ll also begin our important “Data of Candy” analysis then.
Have a great break.
I chose to create a pie chart with the values of the reward minimum for each independent person.
I chose to make a pie chart using the kickstarter data organized by the total backer city because I thought it would be interesting to see in terms of which city backed the most.
In Google Fusion Tables, I chose to create the node chart. It linked the city by the amount donated. I thought this was a new and interesting way to see the data.
I chose to filter the donation data by city.
The visualization is on the second tab of the sheet linked below.