Modeling and Analyzing the Multi-Information Network Propagation Dynamics on Hot Events

Abstract

As the largest online social platform in China, Weibo enables users to freely access and share information, and plays an important role in the dissemination of public opinion. The hot topics on Weibo include multiple pieces of information, the dissemination of which is not an isolated process but affects each other. In consideration of the problem of unclear multi-information propagation rules and insufficient analysis of factors influencing public opinion in real networks, this paper analyzes the multi-information delayed transmission scenario in complex network environments and constructs the Multiple-Information Delay-transmission Susceptible-Forwarding-Immune (MD-SFIFI) model considering the situation that the first message of a hot event has a certain time interval from the release of other messages. Data fitting is conducted to prove the validity of our model. This paper realizes the study of multi-information dissemination law by analyzing the correlation between parameters and information dissemination indicators, and summarizes the multi-information dissemination law, aiming to provide theoretical and data support for the decision making and research of government public opinion response and governance.