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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >Micro-level dynamics of the online information propagation: A user behavior model based on noisy spiking neurons
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Micro-level dynamics of the online information propagation: A user behavior model based on noisy spiking neurons

机译：在线信息传播的微观动态：基于嘈杂尖峰神经元的用户行为模型

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摘要

We develop and validate a model of the micro-level dynamics underlying the formation of macro-level information propagation patterns in online social networks. In particular, we address the dynamics at the level of the mechanism regulating a user's participation in an online information propagation process. We demonstrate that this mechanism can be realistically described by the dynamics of noisy spiking neurons driven by endogenous and exogenous, deterministic and stochastic stimuli representing the influence modulating one's intention to be an information spreader. Depending on the dynamically changing influence characteristics, time-varying propagation patterns emerge reflecting the temporal structure, strength, and signal-to-noise ratio characteristics of the stimulation driving the online users' information sharing activity. The proposed model constitutes an overarching, novel, and flexible approach to the modeling of the micro-level mechanisms whereby information propagates in online social networks. As such, it can be used for a comprehensive understanding of the online transmission of information, a process integral to the sociocultural evolution of modern societies. The proposed model is highly adaptable and suitable for the study of the propagation patterns of behavior, opinions, and innovations among others. (C) 2016 Elsevier Ltd. All rights reserved.
机译：我们开发并验证了在线社交网络中宏观水平信息传播模式形成基础的微观水平动力学模型。特别是，我们在调节用户参与在线信息传播过程的机制级别上解决了动态问题。我们证明了这种机制可以由内源性和外源性，确定性和随机性刺激驱动的嘈杂的尖刺神经元的动力学来现实地描述，这些刺激代表着调节一个人成为信息传播者的意图的影响。根据动态变化的影响特征，随时间变化的传播模式出现，反映了驱动在线用户信息共享活动的刺激的时间结构，强度和信噪比特征。所提出的模型构成了一种微观机制建模的总体，新颖和灵活的方法，由此信息在在线社交网络中传播。因此，它可用于全面了解信息的在线传输，这是现代社会的社会文化发展不可或缺的过程。该模型具有很高的适应性，适用于研究行为，观点和创新等的传播模式。 （C）2016 Elsevier Ltd.保留所有权利。

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