As social media platforms such as Facebook, Twitter, Instagram, and others continue to evolve, we’ve seen a rise in depression among users over the years. Citing this, tech companies and researchers have come up with ways to detect and solve the mental health issues of its users. Now, researchers from Europe have developed an advanced algorithm that can detect depression in 9 out of 10 Twitter users. Here are the details.
A team of researchers from London’s Brunel University and the University of Leicester has come up with an advanced algorithm that can analyze users’ mental conditions based on their Twitter profiles. The algorithm acquires and analyzes 38 distinct data points from a user’s Twitter profile to detect whether they are going through depression or not.
“Anything that’s above 90% is considered excellent in machine learning. So, 88% for one of the two databases is fantastic”, Prof. Abdul Sadka, the Director of the Institute of Digital Futures at the Brunel University, said. “It’s not 100% accurate, but I don’t think at this level any machine learning solution can achieve 100% reliability. However, the closer you get to the 90% figure, the better,” the Director further added.
