Description
Data journalism (also called computer-assisted reporting) refers in part to the analysis of public/government (and other) records. Think of it as an extension of traditional investigative reporting, with emphasis on using public documents in a database or spreadsheet format.
This is largely a skills course with a heavy hands-on component. Upon successfully completing this course, students will feel comfortable examining records using advanced properties of spreadsheets (Google Sheets primarily). You will study data visualization, what works and what doesn’t, and do a little bit of data viz yourself. You also will be expected to think like an experienced journalist by evaluating information critically and applying what you learn to news stories.
I have located an FCC database for all TV stations in the US including Next Gen TV and can use that information to illustrate the number that are on-the-air or planned. I am also thinking of using a tool from my other class called “NodeXL Pro” which is supposed to be able to export social media postings and analyze the language in them to determine positive or negative sentiment.
Since mainstream media isn’t promoting the positive aspects of the new format, many people are getting their information from YouTubers, many of which are up in arms over the Digital Rights Management that has been added to the standard. This appears to be creating a negative opinion on the new standard.
I am interested in what the sentiment actually is and how that could impact the deployment. It might also be interesting to compare it with markets where Next Gen TV is on the air versus areas where it is still being deployed.
Analyze a spreadsheet/database and write roughly an 800- to 1,000-word story. Use 12-point Times New Roman, Microsoft Word doc with one-inch margins and AP Style. This will be a well-researched work of journalism based in part on spreadsheet or database analysis and at least three interviews you conduct. Students are encouraged to begin thinking and working on this project the first week of class. You will upload your data with your story on Canvas.
You will be expected to talk to a wide range of people for your story and to quote several as appropriate. Move beyond traditional interviewing techniques to shadow your subjects, spend time with them in their environments. Use all of your senses to tell the story. (We’ll talk about this a great deal more in class). If you think your particular story will run long or short in length, see your professor/editor well in advance to discuss. Every story is different! So lengths might differ. I’m ok with that.
Beyond the story, two other elements are required. Each is worth 50 points.
At the end of the semester each student will give a brief presentation of findings and show their data to the class. A signup sheet will be distributed in class to sign up.
Each project must also include a simple data visualization.
Be thinking about how you might illustrate your story – photos and graphics – and be ready to discuss those in our budget meetings. The goal is to help the audience easily understand complex data visually.
Data collected using NodeXL to pull from the YouTube API, used to create a pivot table with sentiment analysis. The sentiment analysis was then imported into Tableau to create a chart shown below.
Chart created with Tableau showing sentiment by individual YouTube videos sampled with NodeXL.
List of ATSC 3 TV stations in the US exported from FCC web site on April 1, 2024. Data was imported into Tableau to generate maps.
Maps generated in Tableau presented as PowerPoint slides.