Multi-modal and multi-lingual child safety application

多模式、多语言儿童安全应用

• 批准号: 538430-2018
• 负责人: Inkpen, Diana
• 金额: $ 5.83万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=699470
• 关键词: Multi; modal; multi; lingual; child

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

儿童广泛使用社交媒体最近引发了与网络欺凌和其他对儿童福祉的威胁相关的问题。该项目的主要目标是确定有关儿童行为和生活环境的图像，视频，简短的文字，以及其他可用的元数据从在线通信事件，可用作成人干预的一部分，当情况出现的原因。该项目建立在之前NSERC CRD资助的研究合作基础上，该研究合作对公司非常有用：我们开发的分类算法被集成到其产品中，并创造了9个新工作岗位。 我们建议加强预测儿童行为和心理状况的模型，除了文字交流外，还包括可能有害的图像和视频，以及从儿童设备中提取的与其在线交流相关的元数据。我们还提出了一个新的研究路线，为每个孩子实施个性化的模型，而不是“一刀切”的模型。 我们将开发一套算法程序，从而估计出儿童有发育威胁经历或表现出有问题的心理状况的可能性。我们的算法将使用我们合作者的指导，包括医疗保健和技术专家，以及专门研究儿童行为问题的心理学家和精神病学家