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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Spontaneous emergence of social influence in online systems
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Spontaneous emergence of social influence in online systems

机译：在线系统中社会影响力的自发出现

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摘要

Social influence drives both offline and online human behavior. It pervades cultural markets, and manifests itself in the adoption of scientific and technical innovations as well as the spread of social practices. Prior empirical work on the diffusion of innovations in spatial regions or social networks has largely focused on the spread of one particular technology among a subset of all potential adopters. Here we choose an online context that allows us to study social influence processes by tracking the popularity of a complete set of applications installed by the user population of a social networking site, thus capturing the behavior of all individuals who can influence each other in this context. By extending standard fluctuation scaling methods, we analyze the collective behavior induced by 100 million application installations, and show that two distinct regimes of behavior emerge in the system. Once applications cross a particular threshold of popularity, social influence processes induce highly correlated adoption behavior among the users, which propels some of the applications to extraordinary levels of popularity. Below this threshold, the collective effect of social influence appears to vanish almost entirely, in a manner that has not been observed in the offline world. Our results demonstrate that even when external signals are absent social influence can spontaneously assume an on-off nature in a digital environment. It remains to be seen whether a similar outcome could be observed in the offline world if equivalent experimental conditions could be replicated.
机译：社会影响力会驱动离线和在线人类行为。它遍及文化市场，并在采用科学和技术创新以及社会实践的传播中表现出来。关于在空间区域或社交网络中传播创新的经验研究工作主要集中在一种特定技术在所有潜在采用者中的传播。在这里，我们选择一个在线上下文，该上下文可以让我们通过跟踪社交网站的用户群体安装的一套完整应用程序的流行程度来研究社会影响过程，从而捕获可以在此上下文中互相影响的所有个人的行为。 。通过扩展标准波动比例缩放方法，我们分析了由1亿个应用安装引起的集体行为，并表明系统中出现了两种不同的行为方式。一旦应用程序超过了特定的受欢迎程度阈值，社会影响力过程就会在用户之间引起高度相关的采用行为，这将使某些应用程序达到非凡的受欢迎程度。低于此阈值，社会影响的集体效应似乎几乎完全消失了，这在离线世界中尚未发现。我们的结果表明，即使没有外部信号，社会影响也可以在数字环境中自发地具有开关性。如果可以复制等效的实验条件，是否可以在离线世界中观察到类似的结果还有待观察。

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  • 作者

    Jukka-Pekka Onnela; Felix Reed-Tsochas;

  • 作者单位

    Harvard Medical School, Harvard University, Boston, MA 02115 Harvard Kennedy School, Harvard University, Cambridge, MA 02138 Department of Physics, University of Oxford, Oxford 0X1 3PU, United Kingdom Department of Biomedical Engineering and Computational Science, Helsinki University of Technology, FIN-02015 HUT, Finland CABDyN Complexity Centre, Saied Business School, University of Oxford, Oxford 0X1 1HP, United Kingdom;

    rnCABDyN Complexity Centre, Saied Business School, University of Oxford, Oxford 0X1 1HP, United Kingdom Institute for Science, Innovation and Society, Saied Business School, University of Oxford, Oxford 0X1 1 HP, United Kingdom;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    collective behavior; social networks; fluctuation scaling;

    机译：集体行为;社交网络;波动比例;

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