Mental health data science in rich longitudinal population cohorts

Online social networking sites such as Twitter, Facebook and Instagram have changed the way we live our lives. For recent generations, all aspects of human behaviour, both good and bad, are now reflected in the online as well as the offline worlds. This means that these networks are home to a vast wealth of information about our mental states, which researchers have begun to tap into to improve our understanding of the causes and consequences of mental health and wellbeing. However, although a huge amount of data is available, its true value to medicine can only be realised when we are able to link it to what we know about the lives of specific people in the offline world. Only by doing this can we validate our online measurements of mental health and understand the effect that the social media revolution is having on what it means to be human.

Research chapters will include:
1) Epidemiology of social media use
2) Validating existing social media predictors of mental health and developing new ones using gold-standard ground truth measures in epidemiological samples
3) High-resolution time-series analyses of genetic and environmental influences on mental health over time and in response to events
4) Causal analyses of the impact that social media use has on mental health