Department of Theoretical Physics, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia.
Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia.
Phys Rev E. 2017 Sep;96(3-1):032307. doi: 10.1103/PhysRevE.96.032307. Epub 2017 Sep 5.
In online social dynamics, a robust scale invariance appears as a key feature of collaborative efforts that lead to new social value. The underlying empirical data thus offers a unique opportunity to study the origin of self-organized criticality (SOC) in social systems. In contrast to physical systems in the laboratory, various human attributes of the actors play an essential role in the process along with the contents (cognitive, emotional) of the communicated artifacts. As a prototypical example, we consider the social endeavor of knowledge creation via Questions and Answers (Q&A). Using a large empirical data set from one of such Q&A sites and theoretical modeling, we reveal fundamental characteristics of SOC by investigating the temporal correlations at all scales and the role of cognitive contents to the avalanches of the knowledge-creation process. Our analysis shows that the universal social dynamics with power-law inhomogeneities of the actions and delay times provides the primary mechanism for self-tuning towards the critical state; it leads to the long-range correlations and the event clustering in response to the external driving by the arrival of new users. In addition, the involved cognitive contents (systematically annotated in the data and observed in the model) exert important constraints that identify unique classes of the knowledge-creation avalanches. Specifically, besides determining a fine structure of the developing knowledge networks, they affect the values of scaling exponents and the geometry of large avalanches and shape the multifractal spectrum. Furthermore, we find that the level of the activity of the communities that share the knowledge correlates with the fluctuations of the innovation rate, implying that the increase of innovation may serve as the active principle of self-organization. To identify relevant parameters and unravel the role of the network evolution underlying the process in the social system under consideration, we compare the social avalanches to the avalanche sequences occurring in the field-driven physical model of disordered solids, where the factors contributing to the collective dynamics are better understood.
在在线社会动态中，稳健的标度不变性是导致新的社会价值的协作努力的关键特征。基础的经验数据因此提供了一个独特的机会来研究社会系统中自组织临界性（SOC）的起源。与实验室中的物理系统相比，参与者的各种人类属性以及所传达的人工制品的内容（认知、情感）在这个过程中起着至关重要的作用。作为一个典型的例子，我们考虑通过问答（Q&A）来进行知识创造的社会努力。使用来自此类 Q&A 站点之一的大型经验数据集和理论模型，我们通过研究所有尺度的时间相关性以及认知内容对知识创造过程的雪崩的作用，揭示了 SOC 的基本特征。我们的分析表明，行动和延迟时间的幂律非均匀性的普遍社会动态为自我调整到临界状态提供了主要机制；它导致了远程相关性和事件聚类，以响应新用户到达的外部驱动。此外，所涉及的认知内容（在数据中系统地注释并在模型中观察到）施加了重要的约束条件，这些约束条件确定了知识创造雪崩的独特类别。具体而言，除了确定正在发展的知识网络的精细结构外，它们还会影响标度指数的值和大雪崩的几何形状，并形成多重分形谱。此外，我们发现共享知识的社区的活动水平与创新率的波动相关，这意味着创新的增加可能是自我组织的主动原则。为了识别相关参数并阐明考虑中的社会系统中网络演化在该过程中的作用，我们将社会雪崩与无序固体场驱动物理模型中发生的雪崩序列进行比较，其中对促成集体动力学的因素有更好的理解。
