Information cascade on networks and phase transitions

被引:0
|
作者
Hisakado, Masato [1 ]
Nakayama, Kazuaki [2 ]
Mori, Shintaro [3 ]
机构
[1] Nomura Holdings Inc, Otemachi 2-2-2,Chiyoda Ku, Tokyo 1008130, Japan
[2] Shinshu Univ, Fac Sci, Dept Math, Asahi 3-1-1, Matsumoto, Nagano 3908621, Japan
[3] Hirosaki Univ, Grad Sch Sci & Technol, Dept Math & Phys, Bunkyo Cho 3, Hirosaki, Aomori 0368561, Japan
关键词
Network; Non-equilibrium phase transition; Critical phenomena; Absorption transition; Voting model; HERD BEHAVIOR;
D O I
10.1016/j.physa.2024.129959
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Herein, we consider a voting model for information cascades on several types of networks - a random graph, the Barab & aacute;si-Albert(BA) model, and lattice networks - by using one parameter a; a = 1 , 0 , -1 respectively correspond to these networks. Our objective is to study the relation between the phase transitions and networks using the parameter, a which is related to the size of hubs. We discuss the differences between the phases in which the networks depend. In a not equal -1, without a lattice, the following two types of phase transitions can be observed: information cascade transition and super-normal transition. The first is the transition between a state where most voters make correct choices and a state where most of them are wrong. This is an absorption transition that belongs to the non-equilibrium transition. In the symmetric case, the phase transition is continuous and the universality class is the same as nonlinear P & oacute;lya model. In contrast, in the asymmetric case, there is a discontinuous phase transition, where the gap depends on the network. As a increases, the size of the hub and the gap increase. Therefore, a network that has hubs has a greater effect through this phase transition. The critical point of information cascade transition does not depend on a. The super-normal transition is the transition of the convergence speed, and the critical point of the convergence speed transition depends on a. At a = 1, in the BA model, this transition disappears, and the range where we can observe the phase transition is the same as that in the percolation model on the network. Both phase transitions disappear at a = -1 in the lattice case. In conclusion, as the performance near the lattice case, a similar to -1 exhibits the best performance of the voting in all networks. As the hub size decreases, the performance improves. Finally, we show the relation between the voting model and the elephant walk model.
引用
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页数:19
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