学术报告
Depression Detection on Social Media
发布日期:2022-04-11  来源:   查看次数:

报告时间:2022年4月16日(星期六)下午2:30-4:30

报告地点:线上、腾讯会议号:453-190-378、密码:1515

人:Michael Chau

工作单位:香港大学商manbetx手机版登录注册登录

举办单位:manbetx手机版登录注册

报告简介:

Title: Depression Detection on Social Media

How to manage and provide appropriate treatment to people suffering from depression and emotional distress is a pressing issue. However, many people with depression and emotional distress are not sufficiently recognized and treated; they do not proactively seek help either. Therefore, it is highly desirable to devise a method to effectively and proactively identify these people. Following the design science approach, we propose a novel design called DKMAN (which stands for Domain Knowledge-enhanced Mutual Attention Network) based on deep learning and a knowledge-enhanced mutual attention mechanism to identify people with depression and emotional distress. Our model incorporates both general knowledge and domain knowledge in the learning process through language representations and mutual attention mechanism. The research has important academic contributions and practical implications for depression detection.

报告人简介:

Michael Chau香港大学经管manbetx手机版登录注册登录教授,主持多项由中国国家自然科学基金和中国香港中央政策组等机构资助的研究项目,研究领域包括数据挖掘、社交媒体分析、电子商务、医疗健康等。Michael Chau研究成果发表于MIS Quarterly、JMIS、IEEE TKDE等国际顶级期刊。曾担任MIS Quarterly副主编。

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