Measuring life quality from digital footprints for informed policy decision making

该项目旨在从数字足迹（即互联网和社交媒体数据）中开发新的生活质量衡量标准。它与DCT通路非常吻合。它将采用心理学、管理学和数据科学的跨学科方法，研究数据使用的变化性质，以及新兴的数字数据如何帮助跟踪和监测政策影响。它将产生挖掘公开社交媒体数据的新方法，这将有助于理解社会福利不平等。这可以通过为其“下一代人类数据平台”开发新方法，为合作伙伴CitizenMe的战略路线图做出贡献。数字足迹措施将补充传统的经济指标，后者将提供更准确的政策优先事项指示，从而加强战略决策过程。它将为地方当局利兹市议会的“最佳健康和福祉城市”的雄心壮志增加投入。该项目还将提高人们对数字数据道德的认识，以及监管机构、公司和公众如何共享和使用数字足迹。主管们为这个项目提供了他们在机器学习和人类决策方面的专业知识。管理团队具有丰富的心理学、管理学和计算机科学相结合的跨学科研究经验。由导师团队维护的更广泛的相关合作网络将为该学生提供学术访问机会，这也将有利于本项目的研究发展。这份名单包括但不限于剑桥大学的杰森·伦特弗洛教授（研究社交媒体的地区个性）、桑福德大学的迈克尔·科辛斯基博士（研究数字足迹和人类特征）、剑桥大学的玛格达·奥斯曼教授（研究政策参与）。主办机构利兹大学将通过相关的研究中心，如决策研究中心、研究计算团队、利兹数据分析研究所，以及与艾伦·图灵研究所的合作，为项目研究培训提供心理学、决策科学和数据分析方面的培训和网络。此外，政策利兹团队还将提供有关政策参与的具体培训课程，这将大大有助于被提名学生在未来与其他公共部门合作的知识和技能。

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.