Multi-modal and multi-lingual child safety application

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The widespread usage of social media by children has recently raised problems related to cyberbullying and other threats to their well-being. The main objective of this project is to identify details about childhood behaviours and life-circumstances within images, videos, short pieces of text, and other available metadata from online communication events that can be used as part of a reason for adult intervention when a situation arises. This project builds on a research collaboration conducted on a previous NSERC CRD grant that was really useful to the company: the classification algorithms that we developed were integrated into its product and 9 new jobs were created.We propose to enhance our models for forecasting behavioural and psychological conditions for children to include, in addition to textual communication, images and videos that could be harmful, as well as metadata drawn from children's devices relevant to their online communication. We also propose a new line of research to implement personalised models for each child, rather than a "one size fits all" model.We will develop a set of algorithmic procedures resulting in likelihood estimates that a child is having a developmentally threatening experience or manifesting a problematic psychological condition. Our algorithms will use guidance from our collaborators, including experts in healthcare and technology, and psychologists and psychiatrists specialised in child behaviour issues