- Time: 18:00-19:30
- Date: Monday, 21 March 2022
- Venue: Zhumu (For Zhumu link, please contact: COM@xjtlu.edu.cn)
For many commentators, these systems—which use algorithms to suggest content likely to interest viewers on the basis of their prior viewing histories—represent a fundamentally new way of connecting cultural objects and human beings. Computer scientists, business gurus, and feature writers swoon over the ability to scale the provision of cultural recommendation using big data. In contrast, academics and activists sustain suspicions of filter bubbles and object to how such computational processes seem bound to confirm rather than challenge or develop taste. For these passionate interlocutors, algorithmic recommendation represents the end of humanist criticism as we have known it, the death knell of the Arnoldian“‘best which has been thought and said”. Curiously, however, both the vociferous champions and vehement critics share a common first-principle assumption: that VOD recommender systems are effective, powerful, unprecedented and widely used. Based on a long-term research project, this paper seeks to overturn this consensus, using, among other avenues of inquiry, a mixed-method empirical audience study of VOD users.
Mattias Frey is Professor of Film, Media and Culture in the School of Arts, University of Kent. In his recent and ongoing research, he has taken a critical media industries approach to film (esp. distribution, regulation, exhibition); film and media audiences; promotional media and cultural intermediation (esp. film marketing, criticism); and digital culture (e.g. algorithmic recommender systems). His most recent monograph is Netflix Recommends: Algorithms, Film Choice, and the History of Taste. Profile page: Kent.ac.uk/arts/people/2130/frey-mattias.