This article was originally published in BU Today on March 7, 2019. By Art Jahnke.
Like most stories about data science, this one begins with a very big number: 150 million. That’s roughly how many people, worldwide, subscribe to Netflix. And because Netflix knows what all of those people watch, when they watch, and on what sort of device they watch, that number provides Netflix with the data it needs to determine the narratives, characters, and lengths of the programming to invest in. So when you binge on a season of Stranger Things over a school vacation week, then enjoy a weeknight with the comedy special of Ellen DeGeneres, and finally settle in on a chilly Saturday night to watch the recent Best Foreign Language Film Academy Award winner Roma, you aren’t just consuming art. You’re shaping it.
Netflix programming is refined with algorithms designed to produce popular shows, and then aimed at people whose personal viewing habits suggest that they might like them—two reasons that Netflix original shows are deemed successful 80 percent of the time. That number indicates that the algorithms are working: traditional TV shows have a success rate of about 40 percent. Netflix gets so granular with its data mining that it even tests different thumbnail images on viewers around the world, then presents those viewers with pictures that the data indicates will appeal to their particular demographic.
Similar forces are at work at Spotify, where the musical choices of more than 100 million users point the way to popular success. Spotify’s data allow the online distributor of music to compile a Discover Weekly feature that sends individual users a weekly playlist designed to suit their specific tastes. Like Netflix, Spotify knows what you want, and gives it to you straight. It’s a strategy that doesn’t just please users, it saves the distributors lots of money that once would have been spent on marketing. And just as Netflix produces original video series and movies, Spotify last year started signing licensing deals with independent artists, evolving from being merely a content distributor to a content creator. The only reason that’s possible is because Spotify now knows what to create—thanks to data.
Data analytics, or the science of learning from raw sets of information, isn’t just framing the works of art that we see or listen to. Very often, it becomes the art—incorporated in works of visual art, music, and other mediums. James Grady, a College of Fine Arts assistant professor of art and graphic design, says visual artists tend to use data in one of two ways: in elegant presentations of meaningful information, and to add an element of “aesthetic complexity” to their work. The challenge, he says, is this: “How do you take something that you see in nature, like weather, and create it with code? It’s fascinating how an algorithm can create beautiful patterns like birds flocking in the sky.”
Grady says the past 10 years have seen more visual artists, including some at CFA, working data into their art in creative, and moving, ways. His former student Ivanna Lin (CFA’18) used a database of mass shootings in 2016 to create a calendar with bullet-size holes piercing dates that a shooting occurred.
“Data is extremely powerful,” says Lin, now a designer on the creative team at Education First, an international education company that specializes in educational travel. “I could have simply taken the numbers and displayed them in a traditional format, but I wanted to create an impactful experience instead. I wanted people to walk away feeling something.”