Researchers at MIT are analyzing animated GIFs in an attempt to catalog what they believe to be a unique, Internet-based emotional vocabulary.
An animated GIF—these days often presented in the form of a "reaction GIF"—can make us laugh, but it can also help convey various other complex emotions, including anger, contempt, guilt, or even empathy in an environment that is frequently dominated by text. The advantage of communicating with GIFs, claim the authors of this research, is they can quickly and easily add context in a subtle way that text or emoticons cannot.
The project, called GIFGIF, was created by Travis Rich and Kevin Hu, research students at MIT's Media Lab working across a mix of fields including data science, who hope to capture this specific kind of vocabulary using quantitative methods (i.e., you). Their ultimate goal is to create a tool that lets people explore the world of GIFs by the emotions they evoke, rather than by manually entered tags. The best part? The quantitative nature of the research means you no longer have to feel guilty for looking at funny GIFs all day.
"When you are sent a reaction GIF, it takes only a few seconds for you to 'get it'," explains Rich. "GIFs convey emotions quickly and powerfully. GIFs are sent around on e-mail chains, included in news articles, and are at the core of huge Internet cultures. They are used to express every range of experience, from the joy of the perfect burrito to the heartache of a devastating breakup. So long as we say that language is the meaningful communication of information, GIFs are the alphabet of Internet culture.
"Maybe most importantly, GIFs bring an enhanced ability to empathize. Empathy is deeply lacking in many Internet cultures (as evidenced by the existence of hideous YouTube comments, for instance). GIFs trigger those primal mirror neurons that remind us there is a human on the other side of the connection."
To crowdsource the GIFs effectively, the researchers used an A-B testing framework inspired by another Media Lab project, Place Pulse. A user is presented a random pair of GIFs and asked which GIF better represents one of seventeen emotions. "The user then votes left, right, or 'neither'," says Hu; "we use a scoring algorithm (Bayesian TrueSkill) to score each GIF on a scale from 0 to 1 given an emotion. From those scores, we can create an emotional map of our GIFs, so a user can find the happiest, or angriest, or one with 70 percent excitement and 50 percent contempt. In other words, we find the shape of a GIF in the space of emotions, and provide a map to navigate this space."
There are currently more than 1,024 GIFs on the website, which might seem like a small number, but according to their website, they would rather have "1,000 well-characterized GIFs than 1,000,000 GIFs with only a single vote each." More images will be added automatically once enough votes have been collected to accurately sort the existing GIFs.
"We're hoping to answer some really interesting questions," say the researchers. "Does a GIF's emotional variance impact how it's received? (We have a hunch that emotional variance is why :) is pretty acceptable but ;) is typically an awkward mix of creepy/sexy/playful/pirate-y). Does a GIF's emotional content vary between cultures? For example, what is the best representation of happiness for Germans, compared to a Canadian's impression? And certainly let's not forget, we just want to build a better way to find GIFs that capture that exact emotion you're looking for."
GIFGIF relies on Giphy's API to source their images, but choosing the emotions was a greater challenge, which the researchers explain on their website: "Emotions are tricky—and by no means a trivial (or even possible) thing to quantify. We seek to use emoticons that represent a 'core' or 'basic' emotion so we can understand the atomistic elements of what a gif is conveying... these are by no means definitive, correct, or absolute, but our goal is to make a GIF website—not solve the open questions of universal human emotions."
But what to do with all this data? Some fun ideas include converting a piece of text to GIFs, mapping an image (say, from a webcam) into a GIF, or even automatically parsing the emotion state of movies over time. A teacher of ESL (English as a Second Language) has even been using GIFGIF to teach at an art university in the US. The students are currently learning vocabulary for emotions, and their website makes visualizing the emotions alongside the text a breeze.
"Our more neuroscience-oriented friends have expressed interest in using this data for applications such as autism detection," Hu told Wired.co.uk. "For example, in a clinical setting, by detecting when a user's submission deviates strongly from a stabilized, well-agreed upon result, we may be able to infer their inability to properly read other social interactions." Who knew these often silly and poorly looped images could have the potential to do so much good.
And if all that wasn't awesome enough, they're being pretty open with their data, so if you want to use their results, you probably can. "The first thing we plan to do is open an API to make the data publicly available." Says Rich, "we can't begin to predict what original and creative applications will come out of others being able to incorporate GIFGIF results into their own projects." Just visit their website, or contact them directly.
This story originally appeared on Wired UK.