寻找意义:为什么我们仍然不知道数字数据代表什么

Rebekah Tromble
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引用次数: 3

摘要

早年,研究人员对互联网和数字数据几乎是睁大了眼睛的惊奇和兴奋。数字媒体提供的机会,如网站、公告板和博客,以及后来的社交媒体平台和移动应用程序,似乎是无穷无尽的,研究人员突然被数据淹没了。这些财富是如此之多,以至于需要新的处理、组织和分析方法。然而,在所有的兴奋中,数字研究界似乎在很大程度上忽视了一些基本的东西:所有这些数据实际上代表了什么。在这篇文章中,我认为向前发展,研究人员需要批判性地看待,更加开放,并开发更好的方法来从数字数据中得出推论和更大的意义。我建议,我们需要更仔细地研究这些数据至少在两种意义上所代表的含义:统计和背景。在前一个例子中,我呼吁在数字社会研究中要更加谦虚。在后一种情况下,我呼吁采用启发式模型,以便在我们的工作中进行更大胆、更有力的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Search of Meaning: Why We Still Don't Know What Digital Data Represent
In the early years, researchers greeted the internet and digital data with almost wide-eyed wonder and excitement. The opportunities provided by digital media such as websites, bulletin boards, and blogs—and later by social media platforms and mobile apps—seemed nearly endless, and researchers were suddenly awash in data. The bounty was so great that it required new methods for processing, organizing, and analysis. Yet in all the excitement, it seems that the digital research community largely lost sight of something fundamental: a sense of what all these data actually represent. In this essay, I argue that moving forward, researchers need to take a critical look into, be more open about, and develop better approaches for drawing inferences and larger meaning from digital data. I suggest that we need to more closely interrogate what these data represent in at least two senses: statistical and contextual. In the former instance I call for much greater modesty in digital social research. In the latter, I call for heuristic models that permit bolder, more robust comparisons throughout our work.
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