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ESRC White Rose DTP Collaborative Studentship - Measuring Life Quality from Digital Footprints for Informed Policy Decision Making Leeds University Business School

University of Leeds

Qualification Type: PhD
Location: Leeds
Funding for: UK Students, EU Students, International Students
Funding amount: £17,668 in Session 2022/23
Hours: Full Time
Placed On: 1st February 2023
Closes: 27th February 2023

Session 2023-24 - Closing Date 17:00 (UK time) 27 February 2023 

The online application form can be found at:

https://leeds.onlinesurveys.ac.uk/esrc-white-rose-dtp-collaborative-23

Awards provide fees and maintenance at standard UKRI Rates (£17,668 in Session 2022/23) for eligible applicants.  

This project, in collaboration with Leeds City Council and CitizenMe Ltd, aims to develop new measures of life quality from digital footprints (ie internet and social media data). Recent breakthrough in social data science and machine learning allow easily accessible digital footprints to estimate personal attributes, including their feelings and their psychological and behavioural traits (eg satisfaction, mental health). Citizens’ social wellbeing, like perceived safety and happiness, which is a straight reflection of life quality, is possible to measure through digital footprint data. This provides policymakers with an additional way to look beyond economic statistics and surveys to identify which policies are effective in a timely manner. The project 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. 

Further information on the project and application procedure can be found at:

https://phd.leeds.ac.uk/funding/301-esrc-white-rose-dtp-studentship-measuring-life-quality-from-digital-footprints-for-informed-policy-decision-making 

Further information about how to apply, please contact LUBS Admissions Office:

phd@lubs.ac.uk 

For more information on the project, please contact Xingjie Wei:

x.wei1@leeds.ac.uk

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