S Twitter that could detect signs of these illnesses before clinical diagnosis.
The team of researchers at the University of São Paulo (USP) in Brazil said that preliminary findings from the model suggested the possibility of detecting the likelihood of a person developing depression based solely on their social media friends and followers. The findings are published in the journal Language Resources and Evaluation.
While there are multiple studies involving natural language processing (NLP) focussed on depression, anxiety and bipolar disorder, most of these analysed English texts and did not match Brazilians’ profiles, the researchers said as quoted by news agency PTI.
The first step in this study involved constructing a database, called SetembroBR, of information relating to a corpus of 47 million publicly posted Portuguese texts and the network of connections between 3,900 Twitter users. Reportedly, these users had reportedly been diagnosed with or treated for mental health problems before the survey. The tweets were collected during the COVID-19 pandemic.
“First, we collected timelines manually, analyzing tweets by some 19,000 users, equivalent to the population of a village or small town. We then used two datasets, one for users who reported being diagnosed with a mental health problem and another selected at random for control purposes. We wanted to distinguish between people with depression and the general population,” said Ivandre Paraboni, last author of the article and a professor at USP as quoted by news agency PTI.