Data-driven streamers like Netflix and Amazon Prime Video have expanded into the European screen landscape with a significant appetite for locally produced content. These players leverage advanced data analytics to gain deep customer insights, but they prefer to keep a lid on their algorithmic operations. This article examines how screen workers interact with streaming data despite widespread secrecy. Drawing on interviews and an interface ethnography, I explore the ways these workers access, sense, generate and resist streaming data throughout their creative process. As such, the article provides a framework for understanding the subtle and sometimes contradictory ways that screen workers engage with such data practices. I also demonstrate how researchers can circumvent and lower barriers to access in an industry marked by data secrecy. As a result, this article contributes to discussions about the datafication of cultural production, and it does so with novel insights from the European screen context.

中文翻译：

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Netflix 机器中的摩擦：屏幕工作人员如何与流数据交互

Netflix 和 Amazon Prime Video 等数据驱动的流媒体已经扩展到欧洲屏幕领域，对本地制作的内容有着巨大的兴趣。这些参与者利用先进的数据分析来获得深入的客户洞察，但他们更愿意限制自己的算法操作。本文探讨了屏幕工作人员如何在广泛保密的情况下与流数据进行交互。利用访谈和界面人种学，我探索了这些工人在整个创作过程中访问、感知、生成和抵制流数据的方式。因此，本文提供了一个框架，用于理解筛选工作人员参与此类数据实践的微妙且有时相互矛盾的方式。我还展示了研究人员如何规避和降低以数据保密为标志的行业的准入壁垒。因此，本文为有关文化生产数据化的讨论做出了贡献，并通过来自欧洲屏幕背景的新颖见解来实现这一点。