Exploring TV Seriality and Television Studies through Data-Driven Approaches

Authors

Mirko Degli Esposti
University of Bologna image/svg+xml
Guglielmo Pescatore
University of Bologna image/svg+xml

Synopsis

The chapter discusses the use of data-driven approaches in television studies, which has become possible due to the increasing availability of digital data. Computational techniques can be used to analyze cultural artifacts, gain insights into audience reactions to specific shows or episodes, and investigate patterns and trends in television programming over time. The chapter also highlights the challenges of analyzing television series, which are complex open systems that interact with external factors such as the production process, audience feedback, and cultural and social context. Content analysis, which involves qualitative and quantitative methods based on the coding process and data collection, can be used to analyze various elements of a TV series.

Generative AI is also discussed, which refers to the use of deep multi-modal algorithms to generate new content such as images, speech, and text. Generative methods like Generative Adversarial Networks (GANs) and Stable Diffusion can create new content that is almost indistinguishable from real data. While generating videos is more challenging, Recurrent Neural Networks (RNNs) like LSTMs can capture the temporal dynamics of the scenes to create interesting and promising applications for complex, but short-duration videos.

https://publishing.mediamutations.org/pub/u66zekss#nxnr0rm1nyw

Author Biographies

Mirko Degli Esposti, University of Bologna

Mirko Degli Esposti is full professor in Mathematical Physics at the University of Bologna. Degree in Physics (Bologna, Italy) and PhD in Mathematics (Caltech and PennState, USA). Postdoctoral fellow at the Mathematical Science Research Institute (M.S.R.I), Berkeley. Visiting Professor at the Georgia Institute of Technology. He has been Head of the Math Department of the University of Bologna, and he served as the deputy Rector of the University of Bologna. Recently he has been visiting Professor at the McGill University (Montreal, Canada). He loves mathematical models of information. In his spare time he bikes. 

Guglielmo Pescatore, University of Bologna

Guglielmo Pescatore is full professor of Film and Media Studies at the University of Bologna, where he teaches Entertainment Cultures and Media Economics. His studies on television series gave rise to a strand of research dedicated to narrative ecosystems and vast narratives. Characterized by an interdisciplinary approach, these investigations use qualitative and quantitative analytical tools, some of which are biologically derived.  On these topics he published “Narrative Ecosystems. A Multidisciplinary Approach to Media Worlds” (with V. Innocenti, 2017),  “The Evolution of Characters in TV Series: Morphology, Selection, and Remarkable Cases in Narrative Ecosystem” (2018 with V. Innocenti), Ecosistemi narrativi (2018), “Narration in Medical Dramas I: Interpretative Hypotheses and Research Perspectives” (2019 with M. Rocchi),  “Modeling Narrative Features in TV Series: Coding and Clustering Analysis” (2022 with M. Rocchi).

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Published

July 10, 2023

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Degli Esposti, M., & Pescatore, G. (2023). Exploring TV Seriality and Television Studies through Data-Driven Approaches. In G. Avezzù & M. Rocchi (Eds.), Audiovisual Data: Data-Driven Perspectives for Media Studies. 13th Media Mutations International Conference (pp. 23-40). Media Mutations Publishing. https://doi.org/10.21428/93b7ef64.ec022085