Cataloguing specific URLs, posts, and applications with digital traces is the new best practice for measuring media use and content consumption. Despite the apparent accuracy that comes with greater granularity, however, digital traces may introduce additional ambiguity and new errors into the measurement of media use. In this note, we identify three new measurement challenges when using Digital Trace Data that were recently uncovered using a new measurement framework - Screenomics - that records media use at the granularity of individual screenshots obtained every few seconds as people interact with mobile devices. We label the considerations as follows: (1) entangling - the common measurement error introduced by proxying exposure to content by exposure to format; (2) flattening - aggregating unique segments of media interaction without incorporating temporal information, most commonly intraindividually and (3) bundling - summation of the durations of segments of media interaction, indiscriminate with respect to variations across media segments.

翻译：通过数字痕迹对特定URL、帖子和应用程序进行编目，已成为测量媒体使用和内容消费的最新最佳实践。然而，尽管更高的颗粒度能带来明显的准确性，但数字痕迹也可能在媒体使用测量中引入额外的模糊性和新的误差。在本报告中，我们识别出使用数字痕迹数据时存在的三个新测量挑战，这些挑战是近期通过一种新型测量框架——Screenomics（该框架以数秒间隔获取的个人移动设备交互截图为基础，记录媒体使用行为）发现的。我们将这些考量分别命名为：（1）纠缠——以格式暴露代理内容暴露而产生的常见测量误差；（2）扁平化——在未纳入时间信息的情况下聚合媒体交互的独特片段（最常见于个体内部层面）；（3）捆绑——对媒体交互片段时长进行不加区分的加总，忽视媒体片段间的差异。