Mental health, job quality and workforce participation: evidence from population health research to address complex problems and conflicting policies. Mental disorders such as depression are a major cause of disability. Improving mental health can increase productivity and workforce participation. However, the psychosocial quality of work is a factor that overlays the relationship between work and health. Poor quality work (for example, unreasonable time pressure, insecurity) increases the risk ....Mental health, job quality and workforce participation: evidence from population health research to address complex problems and conflicting policies. Mental disorders such as depression are a major cause of disability. Improving mental health can increase productivity and workforce participation. However, the psychosocial quality of work is a factor that overlays the relationship between work and health. Poor quality work (for example, unreasonable time pressure, insecurity) increases the risk of poor mental health, absenteeism, and exit from the workforce. This project will analyse data following people over time to investigate the long-term health and employment consequences of poor psychosocial job quality, and consider the special case of mature age workers. It will identify those individuals at greatest risk, and factors that can buffer against the adverse effects of poor quality work.Read moreRead less
Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the ....Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the early detection and warning of cyberbullying and approach open a new way to discover interaction patterns with a large number of participants over evolving and complex social networks.Read moreRead less