Computational methods can better help us understand the history and current landscape of the performing arts. For example, we can use network analysis and simulations to study how collaborations within theatre companies develop over time, and how specific management decisions lead to different collaborative patterns. For this, we can take advantage of the records of theatre productions, which are increasingly available in digitized form. Recent advances in open-source AI models can also be used to extract detailed information from videos and texts. For example, we can fine-tune action segmentation models to identify culturally-specific performing conventions in video recordings of performances, and determine how their usage has changed over time.

Speaker info:

Miguel Escobar Varela is Associate Professor at the department of English, Linguistics, and Theatre Studies (ELTS) and deputy director of the Centre for Computational Social Science and Humanities (CSSH) at the National University of Singapore. In his research, he uses digital tools to document and study cultural heritage in Southeast Asia. He is the author of Theater as data (University of Michigan Press, 2021) and has written several articles on digital humanities and Indonesian theatre. A full list of his publications and digital projects is available at https://miguelescobar.com. He is also Associate Editor of the newly established journal Computational Humanities Research (Cambridge University Press).

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