通过算法人种学集中大数据方法的定性研究

Naomi Barnes, Sam Hames
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引用次数: 0

摘要

为了应对定性研究人员在关于大数据、分析、数据化、数据挖掘和算法作用的对话中占据中心位置的挑战,本文描述了一种专注于算法人种志的混合方法研究伙伴关系。在关于在线算法不透明的辩论中,定性研究人员通常主张访问代码。这一标准论述集中了大数据和网络人种学的技术方面。相反,本文概述了一种研究方法,通过与数据科学家的技术专长一起分析算法话语,并利用大数据方法的可负担性来进行定性工作。有人提出,利用定性研究技能调查构成在线社交互动框架的潜在技术过程,是将人们如何理解世界置于大数据研究中心的一种方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Centralising Qualitative Research in Big Data Methods Through Algorithmic Ethnography
Responding to the challenge for qualitative researchers to claim a central place in conversations about big data, analytics, datafication, data mining and the role of algorithms, this article describes a mixed-method research partnership focused on algorithmic ethnography. In the debates about the opacity of online algorithms, qualitative researchers typically advocate for access to code. This standard discourse centralises the technical aspects of big data and networked ethnographies. Instead, this article outlines a research methodology that analyses algorithmic discourses by working alongside the technical expertise of data scientists and utilizes the affordability of big data methods to do qualitative work. The potential for qualitative research skills to investigate the underlying technical processes that frame online social interactions is proposed as a way to place how people understand the world at the centre of big data research.
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