Topological phase transition in network spreading

doi:10.1088/1674-1056/ac7bfa

Abstract This paper investigates information spreading from the perspective of topological phase transition. Firstly, a new hybrid network is constructed based on the small-world networks and scale-free networks. Secondly, the attention mechanism of online users in information spreading is studied from four aspects: social distance, individual influence, content richness, and individual activity, and a dynamic evolution model of connecting with spreading is designed. Eventually, numerical simulations are conducted in three types of networks to verify the validity of the proposed dynamic evolution model. The simulation results show that topological structure and node influence in different networks have undergone phase transition, which is consistent with the phenomenon that followers and individual influence in real social networks experience phase transition within a short period. The infection density of networks with the dynamic evolution rule changes faster and reaches higher values than that of networks without the dynamic evolution rule. Furthermore, the simulation results are compared with the real data, which shows that the infection density curve of the hybrid networks is closer to that of the real data than that of the small-world networks and scale-free networks, verifying the validity of the model proposed in this paper.

Keywords: social network information spreading network structure phase transition

Received: 26 April 2022
Revised: 30 May 2022
Accepted manuscript online: 27 June 2022

PACS:	89.75.Hc	(Networks and genealogical trees)
	89.75.Fb	(Structures and organization in complex systems)
	64.60.aq	(Networks)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61863025 and 62266030), Program for International S & T Cooperation Projects of Gansu Province of China (Grant No. 144WCGA166), and Program for Longyuan Young Innovation Talents and the Doctoral Foundation of LUT.

Corresponding Authors: Fuzhong Nian
E-mail: gdnfz@lut.edu.cn

Cite this article:

Fuzhong Nian(年福忠) and Xia Zhang(张霞) Topological phase transition in network spreading 2023 Chin. Phys. B 32 038901

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