Presented by Cath Sleeman (Nesta)
This study uses a novel dataset of online employee reviews, from Indeed’s UK website, to enhance our understanding of job quality. Keywords within the reviews were extracted and then clustered to form a taxonomy of job quality. It is the first UK taxonomy that is derived from employee reviews and the first to be updatable in real time. Analysis of the taxonomy shows that the emphasis placed on different dimensions of work quality has shifted over time, with a marked increase in references to culture, atmosphere and the broader workplace environment. The study also reveals differences between occupations; workers in some occupations value pay and rewards, while others value the workplace atmosphere and environment.
Cath Sleeman is a data scientist and Head of Data Visualisation at Nesta. Her work aims to show how we can draw new insights from novel sources of big data. Her research has included using job adverts to enrich labour market information (with Jyldyz Djumalieva), and using film credits to reveal gender imbalances in the British film industry. She specialises in creating digital and physical data visualisations, and in 2019 Cath won Silver at the Information is Beautiful Awards for ‘She Said More’.
Chair: Paul Mizen, King’s College London
Discussant: John Forth, The Business School at City, University of London
