The programme looks for depressive content hidden in English language Researchers have developed a software programme that can detect depression in blogs and online texts. The software is capable of identifying language that can indicate a writer’s psychological state, which could serve as a screening too.
Developed by a team headed by Yair Neuman, associate professor of education at Ben-Gurion University (BGU) of the Negev, Israel, the software was used to scan more than 300,000 English Language blogs posted on mental health websites. The programme identified what it perceived to be the 100 “most depressed” and 100 “least depressed” bloggers.
A panel of four clinical psychologists reviewed the samples and concluded that there was a 78 per cent correlation between the computer’s and the panel’s findings. “The software was designed to find depressive content hidden in language that did not mention the obvious terms like depression or suicide,” Neuman said. “A psychologist knows how to spot various emotional states through intuition. Here, we have a programme that does this methodically through the innovative use of ‘web intelligence’.”
For example, the programme spots words that express various emotions, like colours that the writer employs to metaphorically describe certain situations. Words like ‘black’ combined with other terms that describe symptoms of depression, such as sleep deprivation or loneliness, will be recognised by the software as ‘depressive’texts.
Originally conducted for academic purposes, the findings could potentially be used to screen for would-be suicides. The software provides a screening process that raises an individual’s awareness of his or her condition, enables mental health workers to identify individuals in need of treatment and can recommend they seek professional help.