Abstract
For the study of information dissemination in online social networks, most existing information dissemination models include only positive relationships, ignoring the existence and importance of negative relationships, and do not consider the influence of inter-individual relationship polarity on dissemination. To solve these problems, we propose a social network information dissemination model incorporating negative relationships in this paper. Drawing on the state concept of the SIR (Susceptible Infected Recovered) model, the three types of SIR states are subdivided into five sub-states. Combining the advantages of the viewpoint evolution model, the influence of relational polarity on node attitudes is added to the modeling of the propagation process. The experiment proves that the method proposed in this paper can show more specifically the changing trend in the number of propagation nodes with different attitudes and portray the process of information propagation in online social networks.
Keywords
Cite this article
@article{cai-6031,
author = {Meizi Li and Xue Li and Ya Zhang and Jianguo Pan and Ru Yang},
title = {Implementation of a Social Network Information Dissemination Model Incorporating Negative Relationships},
journal = {Computing and Informatics},
volume = {41},
number = {6},
pages = {1510--1540},
year = {2022},
issn = {1335-9150},
doi = {10.31577/cai_2022_6_1510}
}
TY - JOUR AU - Meizi Li AU - Xue Li AU - Ya Zhang AU - Jianguo Pan AU - Ru Yang TI - Implementation of a Social Network Information Dissemination Model Incorporating Negative Relationships JO - Computing and Informatics VL - 41 IS - 6 SP - 1510 EP - 1540 PY - 2022 SN - 1335-9150 DO - 10.31577/cai_2022_6_1510 UR - https://doi.org/10.31577/cai_2022_6_1510 KW - Relationship classification KW - negative relationship KW - information dissemination model ER -
Li, M., Li, X., Zhang, Y., Pan, J., & Yang, R. (2022). Implementation of a Social Network Information Dissemination Model Incorporating Negative Relationships. Computing and Informatics, 41(6), 1510–1540. https://doi.org/10.31577/cai_2022_6_1510