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Dr Anya SkatovaBA(Moscow), MSc(Oxon.), PhD(Nott.)

VC Fellow in Digital Innovation and Well-being

Anya Skatova

Dr Anya SkatovaBA(Moscow), MSc(Oxon.), PhD(Nott.)

VC Fellow in Digital Innovation and Well-being

Member of

External positions

Turing Fellow, The Alan Turing Institute

Research interests

Vice-Chancellor's Fellowship

In my Vice-Chancellor's Fellowship I focus on using large transactional (e.g., banking and retail) datasets to study subjective wellbeing and various factors that can be associated with wellbeing (e.g., personality). National wellbeing is a key priority for government and policy-makers, with measures of subjective wellbeing adopted in the UK to index prosperity of the society. These complement GDP as indicators of societal progress and act as success measures of policy interventions. Wellbeing is commonly measured with self-report questions, e.g., targeting life satisfaction and happiness.

Whilst high profile policy-makers push measures of subjective wellbeing as indicators of the progress of society, their self-report nature provides limited opportunities for exploring factors that affect changes in wellbeing. My fellowship project addresses this gap with three main research questions:

(1) Can wellbeing be reliably indexed through machine records of behaviour?

(2) Can very large datasets provide additional information about the population’s wellbeing over traditional self-reports? 

(3) Can we use very large datasets to understand psychological mechanisms (e.g., personality traits) that can predict and explain variation in subjective wellbeing? 

The outcomes of the project have the potential to change the way companies use large sets of human behaviour data, and the way this data is used by other stakeholders, including academia and government. Understanding when people’s wellbeing changes is crucially important because it can help identify reasons behind those changes, e.g., impact of interventions, policies and reforms. The proposed project builds on a handful of previous studies that employed machine-recorded datasets (e.g., Facebook, banking data) to study psychological traits; and expands this approach to the domain of wellbeing. 

The key innovation of this project is to advance wellbeing science through complementing fixed in time self-report measures of wellbeing (e.g., collected by ONS) with the dynamic measures of changes in wellbeing gained from very large transactional datasets. Extracting a machine-recorded set of wellbeing indices from the data permits infinite nation-level experimentations to understand factors affecting wellbeing, and allows identification of time points where the documented changes in the environment have occurred (e.g., pension reform, change in employment rates). 

Other research

In addition to research on wellbeing and personality, I also employ a range of approaches developed in social, personality and cognitive psychology, behavioural economics and broader decision making literature to understand real life choices and aspects of individual differences that can predict different decisions. My second line of research concerns the psychological underpinnings of cooperation and prosocial behaviour using experimental economics games. I am interested in how different people react to unfair situations, and what factors (e.g., emotions, personality, appraisals) might colour their decisions in social dilemmas. 

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Postal address:
The Priory Road Complex
Priory Road
United Kingdom