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This article questions the way that movie recommendation systems designed to microtarget spectators are thought to operationalize microgenres, highly specific groupings that appeal to narrow niches. If industry leader Netflix’s “altgenres” can track fluid preferences and reconceive audience groupings continuously to effectuate “deep personalization,” such trends towards individualization would undermine canonical genres and their study. But in clarifying the differences and similarities between microgenres, altgenres, subgenres, and cycles, this article situates digital microgenres beside long-standing Hollywood practices, discovers traditional genres enduring at the heart of industry applications of data science, and argues for analytics as a potential boon for film genre studies.
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Gerald Sim (2023) studied this question.
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