Past
Data-driven film industry research
Date & Time
23/10/2024 1:15 pm – 2:45 pm
Vejune Zemaityte
Baltic Film, Media and Arts School (BFM)
Dr Vejune Zemaityte is a Senior Research Fellow in Film Data Analytics at the Baltic Film, Media and Arts School (BFM), Tallinn University, Estonia. Vejune uses data analysis and visualisation techniques, including network analysis, to study global screen industries. She researches film production, theatrical film distribution, film festival circuit, public service television, and historical newsreels. Vejune is particularly interested in diversity, including cultural and thematic content diversity, as well as gender diversity in media production and distribution. Her work is interdisciplinary, data-driven, and industry-facing, often performed with large research teams and in collaboration with industry partners. She currently engages across multiple international projects: Increasing the International Competitiveness of the Film Industry in Small European Markets (CRESCINE), Public Value of Open Cultural Data, ERA Chair for Cultural Data Analytics (CUDAN), and European Universities Alliance for Film and Media Arts (FILMEU).
About the Event
Participation in international film festivals is crucial for films, particularly for independent productions in smaller markets, as they facilitate critical recognition, audience engagement, and distribution opportunities. Our research utilizes the Cinando database, managed by Marché du Film – Festival de Cannes, to conduct data-driven analyses of the festival circuit, modeling festivals as a global network and examining the diversity and public value of festival programming. This talk will discuss some of the quantitative approaches we applied to the film festival database, highlighting not only our results but also the process of working with so-called “found” data created for reasons other than research.
This research is supported by the Public Value of Open Cultural Data project (PRG 1641), funded through the Estonian Research Council, the CUDAN ERA Chair project for Cultural Data Analytics (810961) and ScreenME_Net project (952156), funded through the European Union Horizon 2020 research and innovation program, and the project (101094988), funded through the European Union Horizon Europe funding scheme.
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