The impact of social information on visual judgments
The impact of social information on visual judgments
复制标题
社会信息对视觉判断的影响
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
P. Shah
中科院分区：
文献类型：
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作者：
J. Hullman;Eytan Adar;P. Shah
社会可视化系统的出现是为了支持对不断涌入的开放数据进行集体智能驱动的分析。与许多其他在线系统一样，通常集成社会信号（例如，论坛、投票）来驱动使用。不幸的是，能够提供快速、高精度分析的社会特性也伴随着任何社会系统的缺陷。通过一项涉及300多名受试者的实验，我们研究了社会信息信号（社会证明）如何影响图形感知背景下的定量判断。我们确定无偏见的社会信号如何在非社会环境中导致更少的错误，相反，有偏见的信号如何导致更多的错误。我们进一步反思了系统偏见如何使某些集体智慧的利益无效，并提供了信息级联形成的证据。我们描述了这些发现如何应用于协作可视化系统，以在社会背景下产生更准确的个人解释。
Social visualization systems have emerged to support collective intelligence-driven analysis of a growing influx of open data. As with many other online systems, social signals (e.g., forums, polls) are commonly integrated to drive use. Unfortunately, the same social features that can provide rapid, high-accuracy analysis are coupled with the pitfalls of any social system. Through an experiment involving over 300 subjects, we address how social information signals (social proof) affect quantitative judgments in the context of graphical perception. We identify how unbiased social signals lead to fewer errors over non-social settings and conversely, how biased signals lead to more errors. We further reflect on how systematic bias nullifies certain collective intelligence benefits, and we provide evidence of the formation of information cascades. We describe how these findings can be applied to collaborative visualization systems to produce more accurate individual interpretations in social contexts.