Our activities online don’t only provide a wealth of data useful for marketers and law enforcement — for researchers in Canada, social media may become an important tool for monitoring signs of mental illness, says CBC News. As part of $48 million in federal funding for 76 research teams in Canada, $464,100 was granted to University of Ottawa Professor Diana Inkpen for “social web mining and sentiment analysis for mental illness detection.”
Danika Gagnon, Media Relations for the University says in a recent release that the team includes scientists from University of Ottawa, University of Alberta, and the Université de Montpellier (France), as well as Canada’s Advanced Symbolics, for collecting and sampling the data. The team plans to apply social web mining and sentiment analysis methods to social media data to detect those who are at risk for mental illness. The data will be used to identify negative emotions that are either very strong or that frequently appear over extended periods of time, as well as changes in individual online activities such as suddenly posting very angry or strange messages.
Inkpen says they can then help notify parents, school counselors, or medical professionals whose patients agree to be monitored. Further, Inkpen told CBC that negative emotions could show early signs of possible mental disorders. “It could be depression, it could be anorexia, it could be other kinds of early mental illness signs.”
Just last year, in an effort to combat suicide, Facebook and the University of Washington launched a suicide prevention initiative to help detect and direct those who are exhibiting suicidal tendencies to resources and assistance. Further, social media data from various platforms such as Instagram and Twitter, have increasingly become useful in addressing health matters, from detecting and tracking food-borne illnesses to monitoring underage drinking and gauging patient satisfaction.
The team anticipates that in the future, the algorithms used in the University of Ottawa project may also be used to identify at-risk youth and victims of bullying.
