A close-up view of the homepage of the microblogging website Twitter.
It’s hard to prevent bullying if you don’t know it’s happening. That’s why researchers at the University of Wisconsin-Madison have developed a program that they say is capable of detecting evidence of bullying from among the hundreds of millions of tweets sent each day.
The program uses an algorithm to scour Twitter for words that “mark bullying events.” Out of the 250 million public tweets sent each day, the program usually identifies about 15,000 bullying-related messages.
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The researchers found that while kids aren’t often open in real life about what they are going through, online, they are much more verbose. “What we found, very importantly, was that quite often the victim and the bully and even bystanders talk about a real-world bullying incident on social media,” Jerry Zhu, a professor of computer science at UW-Madison said in a release. “The computers are seeing the aftermath.”
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As GOOD notes, the program could be a way around one of the inherent problems with the reporting of bullying incidents, which is that the targets are often reluctant to report their tormentors, fearing an escalation in the aggression. Its developers hope that not only will their software help alert teachers and parents to bullying early on, but also show victims that they are not alone. “A way victims often make sense of their bullying is by internalizing it. They decide that there’s something bad about themselves — not that these other people are jerks,” Amy Bellmore, a professor of educational psychology at UW-Madison said in the release. “When they’re exposed to the idea that other people are bullied, actually it has some benefit. It doesn’t completely eliminate the depression or humiliation or embarrassment they might be feeling, but it can decrease it.”
Next up, the researchers hope to expand the program to include other social networks, such as Facebook and China’s microblogging site, Sina Weibo.
Kayla Webley is a staff writer at TIME. Find her on Twitter at @kaylawebley, on Facebook or on Google+. You can also continue the discussion on TIME’s Facebook page and on Twitter at @TIME.