State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
Cybersecurity Research Institute, Sichuan University, Chengdu, 610065, China.
Sci Rep. 2018 May 9;8(1):7335. doi: 10.1038/s41598-018-25006-6.
Research on social contagion dynamics has not yet included a theoretical analysis of the ubiquitous local trend imitation (LTI) characteristic. We propose a social contagion model with a tent-like adoption probability to investigate the effect of this LTI characteristic on behavior spreading. We also propose a generalized edge-based compartmental theory to describe the proposed model. Through extensive numerical simulations and theoretical analyses, we find a crossover in the phase transition: when the LTI capacity is strong, the growth of the final adoption size exhibits a second-order phase transition. When the LTI capacity is weak, we see a first-order phase transition. For a given behavioral information transmission probability, there is an optimal LTI capacity that maximizes the final adoption size. Finally we find that the above phenomena are not qualitatively affected by the heterogeneous degree distribution. Our suggested theoretical predictions agree with the simulation results.
关于社会传染动力学的研究尚未包括对普遍存在的局部趋势模仿（LTI）特征的理论分析。我们提出了一个具有帐篷状采用概率的社会传染模型，以研究这种 LTI 特征对行为传播的影响。我们还提出了一个广义基于边缘的分区理论来描述所提出的模型。通过广泛的数值模拟和理论分析，我们发现相变中有一个交叉点：当 LTI 能力较强时，最终采用规模的增长表现出二阶相变。当 LTI 能力较弱时，我们看到一阶相变。对于给定的行为信息传输概率，存在一个最佳的 LTI 能力，可使最终采用规模最大化。最后，我们发现上述现象不会受到异质度分布的定性影响。我们提出的理论预测与模拟结果一致。
