算法电影中的类型观念

IF 2.4 2区 文学 Q1 COMMUNICATION Television & New Media Pub Date : 2023-05-02 DOI:10.1177/15274764231171072
Gerald Sim
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引用次数: 0

摘要

本文质疑为微目标观众设计的电影推荐系统被认为是操作微类型,高度特定的分组,吸引狭窄的利基市场。如果行业领导者Netflix的“另类流派”能够追踪不断变化的偏好,不断重新审视观众群体,从而实现“深度个性化”,那么这种个性化趋势将破坏经典流派及其研究。但在澄清微类型、替代类型、子类型和循环之间的异同时,本文将数字微类型与长期存在的好莱坞实践相提并论,发现传统类型在数据科学的行业应用中经久不衰,并认为分析是电影类型研究的潜在福音。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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The Idea of Genre in the Algorithmic Cinema
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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来源期刊
CiteScore
5.60
自引率
5.00%
发文量
49
期刊介绍: Television & New Media explores the field of television studies, focusing on audience ethnography, public policy, political economy, cultural history, and textual analysis. Special topics covered include digitalization, active audiences, cable and satellite issues, pedagogy, interdisciplinary matters, and globalization, as well as race, gender, and class issues.
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