A framework for linking and sharing social media data for high-resolution longitudinal measurement of mental health across CLOSER cohorts

Interactions on social media have the potential to help us to understand human behaviour, including the development of both good and poor mental health. However, to do the best science we need to know as much as possible about the people who are participating in our research. The CLOSER group of UK longitudinal cohorts include people who have contributed their data to research since birth. By inviting participants in these cohorts to also allow us to derive information from their social media feeds, we will be able to relate this information to gold-standard measures of the behaviours we are trying to understand and to world-class data on other aspects of life. To work out the best way to do this, our project will engage with participants in the Children of the '90s cohort to find out what is acceptable to them in terms of collecting and using their interactions on social media. We will use what we have learnt to develop software that collects and codes social media data in a way that protects the anonymity of participants by scoring Tweets without making the text available to researchers. We will share this software with other CLOSER cohorts to make it easy for them to invite participants to contribute their Twitter data in a safe and secure way. The high-resolution data collected in this way will help us to understand human behaviour and how mental health changes over time. Collecting these data in well known groups of people will also give scientists the information they need to improve the quality of all research using social media.

We will achieve impact in two ways. First, online social media represent a vast untapped repository of data about cohort participants' lives, their behaviour and the environments they are exposed to. These data could be used to make extraordinary discoveries about human health and wellbeing that would be very difficult to achieve by other means. Second, cohort studies have information that is extremely valuable to the wider field of research using social media, because they can provide "ground truth": rich information collected directly from participants that can be used to validate and improve social media coding algorithms. Improving these algorithms could help achieve a step-change in the quality of all research conducted using social media data. We hope that the proof-of-principle dataset that we collect and share as part of this project will demonstrate this and highlight the potential value of linking social media data in other UK cohorts.