Sudden topic propagation scale prediction method and system, processing terminal and medium

Abstract

The invention discloses a sudden topic propagation scale prediction method and system, a processing terminal and a medium, and relates to the technical field of social network information processing. The method comprises: calculating the total influence of messages in the network; constructing a '0' node by using the forwarding quantity as an edge to complement the user forwarding relationship network, and allocating an influence quota according to the user influence ranking of the user in the forwarding network; meanwhile, based on a user influence attenuation mechanism, predicting the sudden topic propagation scale. According to the method, a time attenuation mechanism of the message influence and the user influence is considered at the same time, the message forwarding influence and the user forwarding relationship network are fused, and the propagation scale of the emergency topic in the next stage is predicted by utilizing the user influence. The sudden topic propagation scale prediction system integrating the message forwarding influence and the user forwarding relationship network is innovatively provided, the method provided by the system is high in operability and convenient and fast in data acquisition, and the scale of sudden topic data actually having certain user relationship loss can be effectively predicted.

Description

technical field [0001] The present invention relates to the technical field of social network information processing, and in particular to a method, system, processing terminal, and medium for predicting the propagation scale of sudden topics. Background technique [0002] With the development of artificial intelligence technology and mobile Internet, information disseminated on social networks has become an important content for people to browse the Internet. Social networks are rich in information, express quickly, have multiple channels, and spread rapidly. The sudden topic dissemination based on social networks has Due to the characteristics of fast transmission speed, large transmission impact, and difficult to control the scope of transmission, due to the complexity of the organization system for the prevention and control of sudden topics, it is necessary to predict the scale of the spread of sudden topics on social networks, and to carry out risk prevention and contro...

AI Technical Summary

Problems solved by technology

[0007] (1) The propagation prediction based on the infectious disease model only describes the dynamic change of information dissemination at the first level of information acceptance by users in the network, without considering social individual differences and network topology, and the model is sensitive to the setting of initial values , the accuracy of the model in practical applications is unstable, and it is not suitable for the scene of sudden topic propagation prediction

[0008] (2) The prediction of the scale of communication based on characteristic variables is heavily dependent on human prior knowledge, and the characteristics and mechanisms of different sudden topic communication are not necessarily the same, and there are certain limitations in actual use

[0010] The current method of topic dissemination does not combine information dissemination, network topology and individual differences, and cannot study certain missing relationship data

Images