Rotundo Giulia, Cerqueti Roy, Dhesi Gurjeet, Herteliu Claudiu, Kaur Parmjit, Ausloos Marcel
Department of Statistical Sciences, Sapienza University of Rome, p.le A. Moro 5, 00185 Rome, Italy.
Department of Economics and Social Sciences, Sapienza University of Rome, p.le A. Moro 5, 00185 Rome, Italy.
Entropy (Basel). 2025 Jul 25;27(8):789. doi: 10.3390/e27080789.
This work proposes a hybrid model that combines the Galam model of opinion dynamics with the Bass diffusion model used in technology adoption on Barabasi-Albert complex networks. The main idea is to advance a version of the Bass model that can suitably describe an opinion formation context while introducing irreversible transitions from group (opponents) to group (supporters). Moreover, we extend the model to take into account the presence of a charismatic competitor, which fosters conversion back to the old technology. The approach is different from the introduction of a mean field due to the interactions driven by the network structure. Additionally, we introduce the Kolmogorov-Sinai entropy to quantify the system's unpredictability and information loss over time. The results show an increase in the regularity of the trajectories as the preferential attachment parameter increases.
这项工作提出了一种混合模型，该模型将意见动态的加拉姆模型与用于巴拉巴西 - 阿尔伯特复杂网络上技术采用的巴斯扩散模型相结合。主要思想是改进巴斯模型的一个版本，使其能够适当地描述意见形成的背景，同时引入从反对者群体到支持者群体的不可逆转变。此外，我们扩展了该模型，以考虑存在一个有魅力的竞争对手，它会促使人们回归旧技术。由于网络结构驱动的相互作用，该方法不同于引入平均场。此外，我们引入柯尔莫哥洛夫 - 西奈熵来量化系统随时间的不可预测性和信息损失。结果表明，随着优先连接参数的增加，轨迹的规律性增强。
