Please wait a minute...
Chin. Phys. B, 2026, Vol. 35(5): 056403    DOI: 10.1088/1674-1056/ae5c73
CONDENSED MATTER: STRUCTURAL, MECHANICAL, AND THERMAL PROPERTIES Prev   Next  

Message passing method for social contagion in hypergraphs

Hui Leng(冷卉)1,†, Zhao-Yan Wu(吴召艳)2, and Rong Wang(王荣)11
1 School of Applied Mathematics, Shanxi University of Finance and Economics, Taiyuan 030006, China;
2 School of Mathematics and Statistics, Jiangxi Normal University, Nanchang 330022, China
Abstract  The emergence of hypergraphs has solved the problem that the interactions between nodes are insufficient to describe the complex relationships among multiple individuals. In this paper, we model social contagion with the reinforcement effect on hypergraphs, where hyperedges disseminate information to nodes, and nodes upload information to hyperedges. In order to reduce the complexity of high-order interactions on the propagation, hypergraphs are mapped to factor graphs, where hyperedges are encoded to factor nodes, and the connection between a node and a factor node indicates that the node is located in the hyperedge. Taking into account the heterogeneity of nodes and hyperedges, we establish the message passing evolution equations about each node based on the factor graph. Finally, we carry out numerical simulations by iterating the message passing equations. We find that the probability of the adopted state decreases before the outbreak of social contagion, and the final adopting scale suddenly increases as the transmission rates increase, which are caused by the combined action of high-order interactions and the social reinforcement effect. Significantly, the final adopting scale presents a step-like variation when the adopting threshold of hyperedges changes.
Keywords:  social contagion      hypergraph      message passing method  
Received:  05 January 2026      Revised:  23 March 2026      Accepted manuscript online:  08 April 2026
PACS:  64.60.aq (Networks)  
  87.23.Kg (Dynamics of evolution)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61963019), Fundamental Research Program of Shanxi Province (Grant No. 202403021212007), Project of Shanxi Provincial Department of Education (Grant No. J20250117), and research funds of Shanxi University of Finance and Economics (Grant No. Z18428).
Corresponding Authors:  Hui Leng,E-mail:huileng@sxufe.edu.cn     E-mail:  huileng@sxufe.edu.cn

Cite this article: 

Hui Leng(冷卉), Zhao-Yan Wu(吴召艳), and Rong Wang(王荣) Message passing method for social contagion in hypergraphs 2026 Chin. Phys. B 35 056403

[1] Iacopini I, Petri G, Barrat A and Latora V 2019 Nat. Commun. 102485
[2] Lu J T, Zhang J L, Xue Q, Zhao S Q, Liu Y N, Cui L Q and Meng F Y 2025 Physica A 678130947
[3] Ghoshal G, Zlatic V, Caldarelli G and Newman M E J 2009 Phys. Rev. E 79066118
[4] Ma Y, Xue X, Cai M and Wang W 2020 Chin. Phys. B 29128902
[5] Nian F and Zhang X 2023 Chin. Phys. B 32038901
[6] Higham D J and Kergorlay H L D 2022 SIAM J. Appl. Math. 821987
[7] Liang L D, Cui S X and Liu F Z 2025 IEEE T. Automat. Contr. 711114
[8] Granovetter M S 1978 Am. J. Sociol. 831420
[9] Granovetter M S and Soong R 1983 J. Math. Sociol. 9165
[10] Sun H and Bianconi G 2021 Phys. Rev. E 104034306
[11] Peng H, Qian C, Zhao D D, Zhong M, Han J M, Zhou T and Wang W 2024 Physica A 634129446
[12] Karrer B and Newman M 2010 Phys. Rev. E 82016101
[13] Shrestha M and Moore C 2014 Phys. Rev. E 89022805
[14] Newman M E J 2023 P. Roy. Soc. A-Math. Phy. 47920220774
[15] Leng H, Zhao Y and Wang D 2022 Physica A 587126510
[16] Zachary W W 1977 J. Anthropol. Res. 33452
[1] Optimal synchronization of higher-order Kuramoto model on hypergraphs
Chong-Yang Wang(王重阳), Bi-Yun Ji(季碧芸), and Linyuan Lü(吕琳媛). Chin. Phys. B, 2025, 34(7): 070502.
[2] Identifying important nodes of hypergraph: An improved PageRank algorithm
Yu-Hao Piao(朴宇豪), Jun-Yi Wang(王俊义), and Ke-Zan Li(李科赞). Chin. Phys. B, 2025, 34(4): 048902.
[3] Identification of vital nodes based on global and local features in hypergraphs
Li Liang(梁丽), Li-Yao Qi(齐丽瑶), and Shi-Cai Gong(龚世才). Chin. Phys. B, 2025, 34(10): 108904.
[4] A novel complex-high-order graph convolutional network paradigm: ChyGCN
He-Xiang Zheng(郑和翔), Shu-Yu Miao(苗书宇), and Chang-Gui Gu(顾长贵). Chin. Phys. B, 2024, 33(5): 058401.
[5] Effects of individual heterogeneity on social contagions
Fu-Zhong Nian(年福忠) and Yu Yang(杨宇). Chin. Phys. B, 2024, 33(5): 058705.
[6] Effects of heterogeneous adoption thresholds on contact-limited social contagions
Dan-Dan Zhao(赵丹丹), Wang-Xin Peng(彭王鑫), Hao Peng(彭浩), and Wei Wang(王伟). Chin. Phys. B, 2022, 31(6): 068906.
No Suggested Reading articles found!