Micro-level dynamics of the online information propagation: A user behavior model based on noisy spiking neurons
Authored by Ilias N Lymperopoulos, George D Ioannou
Date Published: 2016
DOI: 10.1016/j.neunet.2016.06.003
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Abstract
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.
Tags
Performance
networks
Contagion
Oscillators
World
Psychological refractory period