a little research....
For pictures see b https://www.google.ca/search?hl=en&site=imghp&tbm=isch&source=hp&biw=1067&bih=510&q=mental+illness&oq=mental+illness&gs_l=img.12..0l10.1601.5626.0.7102.14.10.0.4.4.0.128.914.7j3.10.0....0...1ac.1.64.img..0.14.925.t4iP3wDEC94#hl=en&tbm=isch&q=mental+illness+art
For articles about mental illness see:
https://anaischarles.wordpress.com/2015/04/26/productive-bodies-human-worth-in-the-era-of-capitalism/
http://www.popsci.com/tags/mental-illness
SCARRY CHECK out the video at the bottom of this page
http://www.douglas.qc.ca/section/social-psychiatry-research-and-interest-group-spring-336?locale=en
CDC Report: Mental Illness Surveillance Among U.S. Adults www.cdc.gov/mentalhealthsurveillance/
Do we need a diagnostic manual for mental illness? www.theguardian.com/commentisfree/2012/feb/10/diagnostic-manual-mental-illness
Social media data could be goldmine for predicting mental illness
Posted on Tuesday, Mar 1, 2016
A team of researchers from France and Canada led by Diana Inkpen of the University of Ottawa Faculty of Engineering will explore the use of social media data to help detect and monitor individuals potentially at risk of mental health issues. The project has received a three-year grant from the Natural Sciences and Engineering Research Council of Canada (NSERC).
Social media is everywhere. Internet users are posting, blogging and tweeting about almost everything, including their moods, activities and social interactions.
Using novel algorithms, Inkpen and her team, which includes scientists from uOttawa, the University of Alberta and the Université de Montpellier (France), will take the massive data generated through social media and apply social web mining and sentiment analysis methods to detect those at-risk and their mental state.
“We will investigate one application scenario for our predictive model, which will be used to identify at-risk individuals in online communities. The model will also be used by psychologists and psychiatrists to identify variables related to major mental illness,” explains Inkpen.
The algorithms developed in this project can be adapted for other uses, such as identifying at-risk youth or high school bullying victims.
The research team will partner with the Canadian company Advanced Symbolics, which will collect and sample social media data. Both have expertise in natural language processing, data mining, social media processing and medical informatics, in both English and French.
This is a rare asset, as most current research focuses uniquely on English.
Read the NSERC press release (test this link too)
Media inquiries
Danika Gagnon
Media Relations Officer
Cell: 613-863-7221
danika.gagnon@uOttawa.ca
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