Please note: this event has passed
During the COVID-19 national lockdowns, there was a significant increase in the amount of content UK museums uploaded online. By publishing on social media and platforms like Google Arts and Culture, many museums hoped to reach new, younger, audiences.
This seminar poses the simple question, were they successful?
Platforms’ application programming interfaces (APIs) have made more data available on museums’ digital strategies and online audiences than ever before, opening up new avenues of research. Presenting ongoing work, this talk will explore the results of a large-scale quantitative analysis of museums’ online content, and details how an initial pilot study of 315 UK museums is being expanded to 40,000 museums across Europe.
By contextualising the findings, it will investigate the underlying factors that shape social media metrics—such as ‘likes’, ‘shares’, and ‘comments’—and highlight how they complicate evaluating success online. It is questionable that social media engagement is indicative of the type of audience engagement museums are trying to foster; however, is it possible to use platform data to build more nuanced evaluative tools for the museum sector?
With platforms increasingly acting as mediators between audiences and museums online, this talk explores the difficulties, and future possibilities, this presents for both museums and researchers.
Speaker's Bio: Ellen Charlesworth
Ellen Charlesworth is an AHRC funded PhD candidate at Durham University. Having studied art history at the Courtauld Institute of Art and then data science at Birkbeck, she gained experience designing and evaluating online exhibitions collaborating with the Birkbeck Knowledge Lab, Museum of the Home, and the Venerable English College, Rome.
Her current research asks how we can improve museums online content; using data from museums’ websites and social media she aims to develop more nuanced measures of audience engagement. Her work identifies sector-wide trends in museums’ online content and explores the way this is shaped by both funding guidelines and platforms’ algorithmic interventions.