This article examines an online protest to develop a contextual interpretation of geospatial big data and to challenge the debates on post-truth. In 2016, in support of the local protests against a crude oil pipeline passing through the region, social media users around the world remotely checked in to the Standing Rock Indian Reservation in North Dakota using a technique that we call location spoofing. This collective action thus generated a massive volume of inconsistent locational data that could easily be treated as fake information. Our contextual approach, integrating anthropological methodology, interprets user-generated big data as digital traces of human activities in the broader social–technological network of the involved human and nonhuman actors. This study reveals that the online protesters’ use of location-based features and content recommendation algorithm challenged not only the political and technological authorities but also, at a more profound level, the established ways for determining what is true and who gets to decide what is true for what purpose. We argue that this case of decentralized data generation and dissemination demonstrates an ongoing reconfiguration of the previously established regime of truth that has been monopolized by scientists or politicians. Our unique contextual approach to data interpretation is a pioneering effort to update epistemological assumptions about truth in today’s data-intensive environments. We call on scholars from geography, GIScience, and other disciplines to collectively envision an epistemological shift in our continuous pursuit of knowledge and truth in the so-called post-truth era.

本文研究了一种在线抗议活动，以发展对地理空间大数据的上下文解释，并挑战有关真相的辩论。2016年，为支持当地抗议原油通过该地区的抗议活动，世界各地的社交媒体用户使用了一种称为位置欺骗的技术，远程登录了北达科他州的斯坦丁罗克印第安人保留区。因此，这种集体行动产生了大量不一致的位置数据，这些位置数据很容易被视为伪造信息。我们的上下文方法结合了人类学方法，将用户生成的大数据解释为涉及人类和非人类参与者的更广泛的社会技术网络中人类活动的数字痕迹。这项研究表明，在线抗议者对基于位置的功能和内容推荐算法的使用不仅对政治和技术当局提出了挑战，而且在更深刻的层面上对确定真相以及由谁决定真相的既定方法提出了挑战。出于什么目的是正确的。我们认为，这种分散数据生成和传播的情况表明，科学家或政治家垄断了先前建立的真理制度的正在进行的重构。我们独特的数据解释上下文方法是在当今数据密集型环境中更新关于真相的认识论假设的开创性工作。我们呼吁地理，地理科学和其他学科的学者共同设想在所谓的后真理时代我们对知识和真理的不断追求中的认识论转变。