Grant: Collaborative Research and Development Grants
University of Ottawa
$142,856.00
Social media text mining for detecting behavioral and psychological conditions in children
EF 2017-18
Résumé
The widespread usage of social media by children has recently raised problems related to cyberbullying andother threats to their well-being. VISR.CO has an app that alerts parents to issues their kids are facing online.They analyze the social interactions kids are experiencing on social networks, and search for over 25 alertcategories, from bullying to mental health. Highly accurately detecting these issues that parents care about is adifficult Machine Learning (ML) and Natural Language Processing (NLP) challenge, requiring the latestadvancements in computer science. Additionally, when detecting mental health issues, such as anxiety,depression and self-harm, a clinical expertise is required to understand the underlying conditions and causes.They are currently able to deliver very rudimentary mental health alerts but require both NLP expertise andclinical insight.As of February 12, 2016, VISR.CO has been actively monitoring 9,985 children on behalf of 8,645 parents.VISR.CO has uncovered 850 confirmed cases of bullying (24% success rate), 452 confirmed mental healthconcerns (21% success rate), and 1,018 confirmed substance use concerns (16% success rate). We propose toresearch ways to increase our success rates by using more advanced data-mining techniques. Another challengethat they need to address is to find better ways to deal with the social media texts (such as frequentmisspellings, short-lived idiomatic expressions, and abbreviations) and to account for the dynamic nature oflinguistic expression across social media platforms.If these challenges are addressed, the product will have a competitive advantage by staying up to date,delivering useful alerts to parents, and intelligently framing the unique issues found the online activity of everychild.
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
499383-2016
Name nom
Inkpen, Diana
Department département
Electrical Engineering and Computer Science , School of
Organization id
28
Institution établissement
University of Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2016
Award amount
142856
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Partie
1 & 2
Nb partie
2
Application title
Social media text mining for detecting behavioral and psychological conditions in children
Keyword
NSERC
Application summary
The widespread usage of social media by children has recently raised problems related to cyberbullying andother threats to their well-being. VISR.CO has an app that alerts parents to issues their kids are facing online.They analyze the social interactions kids are experiencing on social networks, and search for over 25 alertcategories, from bullying to mental health. Highly accurately detecting these issues that parents care about is adifficult Machine Learning (ML) and Natural Language Processing (NLP) challenge, requiring the latestadvancements in computer science. Additionally, when detecting mental health issues, such as anxiety,depression and self-harm, a clinical expertise is required to understand the underlying conditions and causes.They are currently able to deliver very rudimentary mental health alerts but require both NLP expertise andclinical insight.As of February 12, 2016, VISR.CO has been actively monitoring 9,985 children on behalf of 8,645 parents.VISR.CO has uncovered 850 confirmed cases of bullying (24% success rate), 452 confirmed mental healthconcerns (21% success rate), and 1,018 confirmed substance use concerns (16% success rate). We propose toresearch ways to increase our success rates by using more advanced data-mining techniques. Another challengethat they need to address is to find better ways to deal with the social media texts (such as frequentmisspellings, short-lived idiomatic expressions, and abbreviations) and to account for the dynamic nature oflinguistic expression across social media platforms.If these challenges are addressed, the product will have a competitive advantage by staying up to date,delivering useful alerts to parents, and intelligently framing the unique issues found the online activity of everychild.