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External Validity of Estimates of Social Distance

机译:社会距离估计的外部有效性

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Social discounting underlies individual altruistic decision-making, and it is frequently measured as the amount of hypothetical money one is willing to forgo for another person as a function of social distance. In the classic social discounting task, individual participants are asked to imagine their friends along a continuum of social distance, that is then used to estimate participant's social discounting rate. While an ever-growing proportion of social interactions takes place over social media, no research has yet characterized social discounting in that context. Moreover, no research has estimated social discounting rate using real persons' social distance, instead of the hypothetical continuum described above. Using existing social media indicators of social distance, it is now possible to estimate social discounting rate based on real people, which may lead to more accurate social discounting measurements and may expand the discounting model to real-life situations. Specifically, using computer algorithms to estimate the social distance from social media data makes it possible to assess the utility of numeric social distance indicators and the most appropriate ways to represent them. The proposed study examined the extent to which a hyperbolic model for social discounting fits social distance information retrieved from Facebook pages; and assessed whether there were differences in discounting rate when real or hypothetical social distance is used; also to further investigate whether discounting rates based on real persons are in fact based on perceived social distance by the participant, or on the imaginary social distance scale (i.e., an experimental artifact.).;It was found that the social discounting model can be applied in the social media context, even when real Facebook friends' profiles were used as substitutes of numeric social distance indicators. Additionally, people showed similar altruistic tendencies in both the numeric and profile social discounting tests on the Facebook environment. These findings were qualified, however, by a high rate of nonsystematic data for the profile group; a rate much higher than traditional numeric paradigm. This discrepancy suggested that the allocation rates between numeric and profile approaches need further investigation to determine the factors affecting individuals' generosity as a function of social distance indicators.
机译:社会贴现是个人无私决策的基础,它经常被衡量为一个人愿意为另一个人放弃的假设金钱的数量,作为社会距离的函数。在经典的社交折扣任务中,要求个体参与者沿着社交距离的连续性想象他们的朋友,然后将其用于估算参与者的社交折扣率。尽管社交互动的比例在社交媒体上不断增长,但在这种情况下,尚无任何研究能描述社交折扣。此外,没有研究使用真实人的社会距离来估计社会折现率,而不是上面描述的假设连续体。使用现有的社交距离社交距离指标,现在可以根据真实人群估算社交折扣率,这可以导致更准确的社交折扣测量,并且可以将折扣模型扩展到现实生活中。具体而言,使用计算机算法来估计来自社交媒体数据的社交距离,可以评估数字社交距离指示器的效用以及最合适的表示方式。拟议的研究检查了针对社会折扣的双曲线模型在多大程度上适合从Facebook页面检索的社会距离信息。并评估在使用真实或假设的社会距离时折现率是否存在差异;还进一步研究了基于真实人的折扣率实际上是基于参与者感知的社会距离,还是基于假想的社会距离量表(即实验性人工产物)。即使在使用真实的Facebook朋友个人资料替代社交距离数字指示器时,也可以在社交媒体环境中使用该功能。此外,人们在Facebook环境的数字和个人资料社会折扣测试中都表现出类似的利他主义倾向。但是,个人资料组的非系统性数据占很高的比例,这证明了这些发现。这个比率远高于传统的数值范式。这种差异表明,数字方法和个人资料方法之间的分配率需要进一步研究,以确定影响个人慷慨程度的因素,这些因素是社会距离指标的函数。

著录项

  • 作者

    Jiang, Linle.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Social psychology.;Information science.
  • 学位 M.S.
  • 年度 2018
  • 页码 79 p.
  • 总页数 79
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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