How can we trace intangible historical phenomena, such as worldviews, cultural representations, or cultural-political movements through large-scale audiovisual archives? While the hermeneutic tradition of close reading has long provided a foundation for analyzing small-scale historical materials, the rise of digital sources presents new challenges and opportunities. When engaging with vast datasets, the intuitive processes of qualitative analysis must be made explicit, translating human insights into computational terms. This requires us to define the phenomenon under study more explicitly, identify its measurable units within the data, and critically evaluate how both the available data and applied methods allow us to address the research question.
Drawing on my ongoing collaborative work on Soviet newsreels (1945-1992) this presentation explores the role of computational methods in research of cultural historical phenomena. As a historian working with audiovisual materials, I view them as traces of past cultural, technological, informational activities, constantly seeking ways to capture the underlying phenomena they represent. I will focus on examples from three collaborative projects—A Framework for the Analysis of Historical Newsreels, Soviet View of the World, and Quantifying Leninism—which illustrate combining qualitative and quantitative inquiries and Artificial Intelligence with human thinking. Specifically, I will discuss the use of multidimensional vector embeddings to analyze shifts in visual discourse over time and how Large Language Models can be employed to trace the presence and transformation of Leninism. These case studies invite reflection on the boundaries and possibilities of quantifying culture through computational means.
Lecture within the Open Research Colloquium Digital History
Time: Wednesday, 13 November 2024, 4:15-5:45pm CET
Place: via Zoom – Request access via email (digitalhistory@hu-berlin.de) or Mailinglist
Additional materials:
Oiva, Mila, Ksenia Mukhina, Vejune Zemaityte, Andres Karjus, Mikhail Tamm, Tillmann Ohm, Mark Mets, et al. “A Framework for the Analysis of Historical Newsreels.” Humanities and Social Sciences Communications 11, no. 1 (April 25, 2024): 1–15. https://doi.org/10.1057/s41599-024-02886-w.
Oiva, Mila, Tillmann Ohm, Ksenia Mukhina, Mar Canet Solà, and Maximilian Schich. “Soviet View of the World. Exploring Long-Term Visual Patterns in ‘Novosti Dnia’ Newsreel Journal (1945-1992).” Journal of Cultural Analytics 9, no. 4 (July 18, 2024). https://doi.org/10.22148/001c.118495.
Ohm, Tillmann, Mar Canet Solá, Andres Karjus, and Maximilian Schich. “Collection Space Navigator: Interactive Visualization Interface for Multidimensional Datasets,” 2023. https://collection-space-navigator.github.io/.
Fridlund, Mats, Mila Oiva, and Petri Paju, eds. Digital Histories. Emergent Approaches within the New Digital History. Helsinki: Helsinki University Press, 2020. https://doi.org/10.33134/HUP-5.
A test dataset: fractions of Estonian newsreels in Collection Space Navigator: https://csn.kinokroonika.ee/
OpenEdition schlägt Ihnen vor, diesen Beitrag wie folgt zu zitieren:
Digital History Berlin (Redaktion) (11. November 2024). Mila Oiva: Chasing Leninism with AI. Using Computational Methods to Trace Cultural Phenomena through Historical Audiovisual Materials. Digital History Berlin. Abgerufen am 24. März 2025 von https://doi.org/10.58079/12nh7