Measuring life quality from digital footprints for informed policy decision making

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This project aims to develop new measures of life quality from digital footprints (i.e., Internet and social media data). It fits nicely with the DCT pathway. It will employ interdisciplinary approaches from psychology, management, and data science to examine the changing nature of data usage and how emerging digital data can help track and monitor policy influence. It will generate new methodologies for mining open social media data, which will help the understanding of the society in social wellbeing inequalities. This can contribute to the strategic roadmap of partner CitizenMe by developing new methodologies for its "next generation human data platform". The digital footprint measures will complement the traditional economic metrics, which will provide a more accurate indication of policy priorities, hence enhancing the strategic policy making process. It will add inputs to the local authorities Leeds City Council's 'Best City of Health and Wellbeing' ambition. This project will also raise awareness about digital data ethics and how digital footprints can be shared and used by regulators, companies, and the public. The supervisors provide their expertise in machine learning and human decision-making for this project. The supervisory team has rich experience in interdisciplinary research combining psychology, management and computer science. Broader relevant collaboration networks maintained by the supervisory team will provide academic visiting opportunities for the student, which will also benefit the research development of this project. This list includes, but is not limited to, Prof Jason Rentfrow at the University of Cambridge for regional personality from social media, Dr Michal Kosinski at Sandford University for digital footprints and human traits, Prof Magda Osman at the University of Cambridge for policy engagement. The host institution, the University of Leeds, will provide training and networks in psychology, decision science, and data analytics for the project research training through relevant research centres such as the Centre for Decision Research, Research Computing Team, and the Leeds Institute for Data Analytics, and also its partnership with the Alan Turing Institute. Additionally, specific training courses on policy engagement will also be offered by the Policy Leeds team will significantly contribute to the nominated student's knowledge and skills in collaborating with other public sectors in the future.