Film Remakes, Intercultural Communication, Digital Innovation,
AI Software: Möbius Trip, Illustrations, Photography, Digital Narrative
Work in Progress
I propose an edited book project featuring a multimodal digital approach to cross-cultural comparative analysis of film remakes. I will gather international scholars from different fields (e.g. Media and communication, intercultural communication, digital humanities) to work collaboratively on the Italian movie Perfect Strangers and its 23 worldwide remakes worldwide. The participants will have access to my deep learning software, the Möbius Trip, to gather and manage data.
Reverse-engineering and Gradational Assemblage
A Deep-learning Approach to Transnational TV series Adaptations
ABSTRACT
Based on a deep-learning approach to transnational TV series adaptations, we deconstruct, restructure, analyze, and compare cultural and cinematographic elements through data mining. Showcasing eight episodes of the American TV series Law & Order Criminal Intent and their equivalent French remake, Paris Enquêtes Criminelles, we seek recurring patterns of shot scales in conjunction with gender and characters' expressions of emotion to uncover and compare cultural representation and cinematographic trends in France and the US.
We rely on our AI toolkit, the Möbius Trip, to conduct our research. The Möbius Trip is a multimodal analysis engine based on machine learning techniques used to predict elements in audiovisual narration. The toolkit measures the screen time of male and female characters, identifies expressions of emotion[1], and recognizes shot scales[2].
Based on Lev Manovich's concept of reverse-engineering [3], we identify, isolate, and quantify each element. Relying on Franco Moretti's Distant Reading[4] model, we conceptualize different levels of reading of the audiovisual text by gradually zooming in on the data. We focus on shot scales between the French and American shows (figure 1). Next, we zoom in and analyze gender through shot scales. Lastly, we achieve in-depth reading by looking at the character's emotions through shot scales (Figure 2).
We describe our approach as a Large-Scale Granularity Reading (figure 3). That is, the gradational assemblage of a wide range of elements with each other at a large scale to obtain comprehensive, precise, and complex recurring televisual patterns.
[1] Six universal expressions of emotion: Anger, Disgust, Fear, Happiness, Sadness, and Surprise
[2] Shot scales ranging from Big Close-up (BCU), Close-up (CU), Medium Close-up (MCU), Medium Long Shot (MLS), Long Shot (LS), and (Very Long Shot (VLS)
[3] Manovich, L. (2013). Visualizing Vertov. Russian Journal of Communication, 5(1), 44–55. https://doi.org/10.1080/19409419.2013.775546
[4] Moretti, Franco. 2015. Distant reading. London: Verso.
Perfect Strangers: 23 remakes worldwide
Paper #2: in progress
The Influence of Film Techniques on Genre in Transnational TV series Adapatation
ABSTRACT
Born from a collaboration between a humanities scholar and an artificial intelligence engineer, the Möbius Trip is a deep-learning multimodal toolkit that can predict TV series genre based on the combination of color, light, rhythm, and music. Following the tradition of formalist film theorists concerned with the technical elements of motion pictures, and Cultural Analytics, which focuses on computational, visualization, and big-data methods, we seek patterns in the film-making cultural tradition between the US and France. Our results indicate that Transnational TV series Adaptations, the transfer of a show into another culture, also implies a transfer in genre. Our goal is to offer a potent toolkit that can help TV series adaptors make more intentional decisions when adapting a show and make the adapted show more successful.