Raise your hand if you’ve been robocalled during the past week: A breakdown of complaints to the FTC
Note from the Editor: This post is part of a series, written by students of the Spring 2019 Data Journalism I course in the Newmark Graduate School of Journalism at CUNY, in which they share their work and thought process. Each week we have a Data Fest in which two of the class reporters present a data set, along with a brief critique and overview of what they did and discovered.
A robocall is an automated telephone call which delivers a recorded message. Now this is where the call can vary as some are important robocalls, like an appointment reminder or a reminder to refill on a medication.
Then again, you’ll get the occasional “ Congratulations! you’ve won a getaway cruise! Just give us your social security and credit card information.”
I’ve always liked looking for quirky data, sometimes there can be interesting information out there.
For my data journalism course at the Craig Newmark Graduate School of Journalism at CUNY, one of the assignments was to find a data set available to us and present it to our classmates in our weekly Data Fest presentation. But on top of finding our data set, we had to clean it, because some public data is messy (trust me), sort it out, analyze it and see what we found.
My original plan was to analyze data for something else, I don’t remember what was it at this point.
However, it all changed after watching the robocall segment on Last Week Tonight with John Oliver. He made robocalls an interesting topic. At the end of the segment, I was left curious and wanted to know more. That’s when I decided to search up robocall data. I went to Google and type “robocall complaints xls”. Yes really, that’s how I typed it.
A trove of data in hands of the FTC
I found data for 2017 on the Federal Trade Commission (FTC) website. But I faced a problem after downloading the file, it was to large. It slowed down my computer and whenever I tried working on it through Excel, it froze and took forever to load.
Next, I used Google sheets but that was no use either because it would crash my Chrome browser when importing the data. I realized this wasn’t going to work.
I decided to focus on weekly complaints of these calls for 2019. I worked with the data from March 22–28, 2019. It was the most recent at the time.
Something I had to realize was that this data was a combination of “robocalls” and “Do Not Call” complaints.
I had complaints from all 50 states. But I focused on New York State because I am from this state.
I separated the complaints by day and put the data for each date into individual sheets. In this way I made sure that I would not mix things up or get confused.
After that, I summed up the type of complaints that were registered for the entire week on a new sheet. These were the results…
Breaking it down leads to more relevant questions
Something that stands out to me was what kind of call was made to be considered a “No Subject Provided” category. Who usually makes that decision, the person from the FTC logging the information or the person who called?
“Medical and Prescription” also caught me by surprise because I expected people to usually liked to be reminded about their medication.
To go even further about the complaints, I would’ve narrowed them down by area code. There, I could analyze the population, race and ethnicity and average age of the people living in their respective area code. Why is one area targeted more frequently than a neighboring area code?.
It was a fun experience to analyze this data. It doesn’t fail to amaze me how many calls a State can receive in only one week.
If there’s one thing everyone can agree on is that robocalls are annoying.
