Audience Dissemination Response Law and Action Mechanism Based on Internet Rumor Computer Big Data

Abstract

Various novel Internet rumors have also emerged. This article mainly researches the audience dissemination response law and the mechanism of action. This paper constructs a model of network rumor spreading. In the homogeneous network, we know that for the rumors that the initial infection rate is large, the increase caused by the herd phenomenon is not very large. For heterogeneous networks, we need to separately examine the increase of nodes and sparse nodes in the network under different initial infection rates. With the change of time, the number of nodes in each state will change due to interaction. When an ignorant person contacts a communicator, the ignorant person will be converted into a rumor communicator with a certain probability. Affected by the memory ability of individual user nodes, each online rumor support node and online rumor opposition node becomes an online ordinary user node with a constant probability f. Affected by the rumor support node, an online ordinary user node is transformed into a receiving unread node by a rumor support node with probability β at time t. Experimental data shows that when the herd effect is not considered, it is found that the transmission peak is 0.4328 at t = 10. When the herd effect is introduced, the spread of rumors reaches the transmission peak 0.5431 at t = 8. After the introduction of the herd effect, the peak value increased by 25.5%, and the time to reach the peak was shortened by 20%. The results show that computer big data technology has a significant inhibitory effect on the spread of Internet rumors.