Love them or hate them, GIFs rule the web—and a pair of graduate students at the MIT Media Lab want to turn them into a language. Travis Rich and Kevin Hu started a site that uses human brainpower to quantify the emotional content of animated GIFs (like the two below), as a side project. But their site, GIFGIF, is no joke.
“We were talking about GIFs one day,” Hu told Quartz, “and we realized that they’re becoming more and more serious of a medium. They’re more popular, they’re used for more things.” Buzzfeed, for example, recently used GIFs to explain what was going on in Ukraine—reaching an audience that otherwise might have ignored the news. “And we realized,” Hu said, “that we could quantify this usage.”
The site, where visitors pick which of two GIFs relates better to a particular emotion, is powered by another MIT Media Lab project’s platform. Place Pulse used the multiple-choice A/B voting system to assign emotions to pictures of different cities, allowing researchers to quantify, for example, how “sad” or “unsafe” people felt when looking at pictures of Rio de Janeiro.
But Rich and Hu, who worked on separate teams but sat near each other (and the Place Pulse group) in the lab, decided to harness the system for their own purposes, to create a visual database of emotion. “It’s the same idea,” Rich said. “Taking something that’s very easy for humans to read—emotion—and translating it for computers.” While humans have no trouble deciphering what a GIF “means,” the same task is impossible for a computer.
GIFs that express happiness, he said, are almost universally agreed upon, but the emotion of “relief” showed much more variation. “So maybe,” Rich said, “situations where you’re expressing relief are the most likely to be misinterpreted by members of a different cultural group.” But even with cultural variation, GIFs are proving to be more universal than the written word: The researchers recently heard from an ESL teacher who’s using GIFGIF to teach students the words for different emotions.