注:痕量数据收集的社会材料视角:民主化和限制偏见的策略

Dipto Das, Arpon Podder, Bryan C. Semaan
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引用次数: 3

摘要

研究人员大量使用在线平台收集跟踪数据,即数据捕获用户在社会技术系统上和与之交互的数据。人机交互学者在分析边缘化社区的数据时,强调了反身性的作用。从社会材料的角度出发,我们强调了涉及搜索短语和api列表的数据收集方法如何在数据集中嵌入研究人员的立场、观点和偏见。在本文中,我们反思了两篇论文的数据收集方法,这两篇论文研究了在问答网站Bengali Quora上被社会历史边缘化的孟加拉社区。我们说明了如何将推荐系统和数据标签工作者包括在数据收集过程中,以实现民主化和限制偏见,同时扩大和背景化用于研究的跟踪数据集。
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Note: A Sociomaterial Perspective on Trace Data Collection: Strategies for Democratizing and Limiting Bias
Researchers heavily use online platforms for collecting trace data, i.e., data capturing user interaction on and with sociotechnical systems. Human-computer interaction scholars have highlighted the role of reflexivity while analyzing such data in the case of marginalized communities. Drawing on sociomaterial perspectives, we highlight how data collection approaches involving lists of search phrases and APIs can embed researchers’ positionality, perspectives, and biases within the datasets. In this note, we reflect on the data collection approaches of two papers that studied the sociohistorically marginalized Bengali communities on the question-and-answer site Bengali Quora. We illustrate how recommendation systems and data labeling workers can be included in the data collection process to democratize and limit bias while broadening and contextualizing the trace datasets for research.
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