In the wake of the 2018 Facebook–Cambridge Analytica scandal, social media companies began restricting academic researchers’ access to the easiest, most reliable means of systematic data collection via their application programming interfaces (APIs). Although these restrictions have been decried widely by digital researchers, in this essay, I argue that relatively little has changed. The underlying relationship between researchers, the platforms, and digital data remains largely the same. The platforms and their APIs have always been proprietary black boxes, never intended for scholarly use. Even when researchers could mine data seemingly endlessly, we rarely knew what type or quality of data were at hand. Moreover, the largesse of the API era allowed many researchers to conduct their work with little regard for the rigor, ethics, or focus on societal value, we should expect from scholarly inquiry. In other words, our digital research processes and output have not always occupied the high ground. Rather than viewing 2018 and Cambridge Analytica as a profound disjuncture and loss, I suggest that digital researchers need to take a more critical look at how our community collected and analyzed data when it still seemed so plentiful, and use these reflections to inform our approaches going forward.

在2018年Facebook–Cambridge Analytica丑闻之后，社交媒体公司开始限制学术研究人员通过其应用程序编程接口（API）访问最简单，最可靠的系统数据收集方式。尽管这些限制已被数字研究人员广泛谴责，但在本文中，我认为变化相对较小。研究人员，平台和数字数据之间的潜在关系基本保持不变。平台及其API一直都是专有的黑匣子，从未打算用于学术用途。即使研究人员似乎可以无休止地挖掘数据，我们也很少知道手头的数据类型或质量。此外，API时代的繁盛使许多研究人员在进行工作时几乎不顾严谨，道德，或关注社会价值，我们应该从学术研究中期待。换句话说，我们的数字研究过程和输出并不总是占据较高的位置。我建议不要将2018和Cambridge Analytica视为深刻的混乱和损失，而是建议数字研究人员应该更批判性地看待社区似乎仍然如此丰富时如何收集和分析数据，并使用这些思考来指导我们的方法前锋。