Research collaboration: evaluating events data for cultural analytics
13 February 2024
This innovative project by an interdisciplinary team from the universities of Edinburgh and St Andrews investigated how Covid-19 affected the cultural events sector in Edinburgh.
Dr Suzanne R. Black, Research Fellow in Data Service Design, University of Edinburgh, describes the background to the project “Towards Large-scale Cultural Analytics in the Arts and Humanities”.
The remit of the project was to understand the long tail of data left by the tens of thousands of cultural events that happen across the UK every week, from theatre to comedy, and festivals to exhibitions, and to explore the opportunities for researchers to analyse trends, understand the contribution the UK creative industries make to our culture and society, and plan ahead for the future. This project brought together expertise in data science and understanding of the cultural landscape in Edinburgh.
Analysing the dataset
We worked with events data providers Data Thistle, who provided us with a dataset of events located in the area delimited by the Edinburgh and South-East Scotland City Region Deal and taking place between November 2017 and May 2022. Rosa Filgueira, who began the work while a research fellow at EPCC, led on understanding and analysing the dataset by ingesting the data files into a Python 3.9 environment using pandas DataFrames, creating entity diagrams to understand the structure of the dataset and its main features, and creating Jupyter Notebooks to enable a variety of analyses to be conducted on the dataset – or subsets of it – delimited by city, month and category of event.
Once these were in place, we were able to ask specific research questions of the data. We sought to answer how events data at scale can be used to quantify the financial and social effects of the Covid-19 pandemic on the cultural events sector in Edinburgh. To do this, we analysed the changes in event provision in Edinburgh in August from 2018, 2019, 2020 to 2021 and developed an algorithm to estimate ticket revenue.
Results
We revealed an estimated 97.3% fall in ticketing revenue between 2019 and 2020. Additionally, the effects that pandemic restrictions had on different categories of event reveal a disparity in how different audience sectors were affected, with ‘Visual Art’ and ‘Days Out’ showing most resilience and ‘Theatre’, ‘Comedy’ and ‘LGBT’ events being most reduced. We connect disproportionate event provision to inequalities in how sectors of society are affected by public health legislation in different ways. We found that events data are a rich but heterogenous source of information regarding the cultural and creative economy, which is not yet routinely used by researchers.
The team comprised Professor Melissa Terras, Professor of Digital Cultural Heritage, University of Edinburgh, Professor Lesley McAra, Professor of Penology, University of Edinburgh, Professor Mark Parsons, Director of EPCC and Dean of Research Computing, University of Edinburgh, Dr Rosa Filgueira, Lecturer in Computing Science, University of St Andrews, and myself.
This work was funded by the UK’s Arts and Humanities Research Council under their “Scoping future data services for the arts and humanities” scheme.
Author
Dr Suzanne R. Black, Research Associate, Creative Informatics, University of Edinburgh
https://creativeinformatics.org/bio/suzanne-black/
Further information
Related animations:
Performance places per category in Edinburgh during August (2018–2021)
https://rosafilgueira.github.io/case_study_covid/freq_performance_places_category_edinburgh_August.html
Performance places in Edinburgh during August (2018–2021)
https://rosafilgueira.github.io/case_study_covid/performance_places_edinburgh_August.html