A modeling method of multi-information propagation model in social network

Abstract

The invention discloses a modeling method of a social network multi-information propagation model. The method extends into a plurality of messages on the basis of a single message propagation model, introduces different associations among the messages and memory attenuation of users, and obtains the final evolutionary stable state of information propagation. The invention combines the mutual influence among multiple messages, and is closer to the actual situation of the common transmission of multiple messages in the social network. The present invention is socially based on message network framework models and demonstrates the phenomenon of multi-information dissemination in social networks. The invention improves the accuracy of multi-information propagation prediction in the network, and provides effective model support for different aspects such as topic prediction, public opinion control, disease control, network marketing, propaganda strategy of products or advertisements put outby a plurality of enterprises, and the like.

Description

technical field [0001] The invention belongs to the technical field of information dissemination models, and in particular relates to a modeling method of a social network multi-information dissemination model. Background technique [0002] With the rapid development of Internet technology and the emergence of online social networks, the speed of information dissemination is faster, the scope of influence is wider, and the amount of information is also larger. Researchers have extensively used complex networks to describe the real-world communication dynamics, and information dissemination in the network is also a complex dynamic process, which is interactively affected by many factors, such as the topology of the network, the influence of information publishers, and the influence of users. interest preferences, the characteristics of the information itself, and so on. Understanding the dissemination process in complex networks is a core issue in the field of network scienc...

AI Technical Summary

Problems solved by technology

However, in the dissemination of topics on real social networks, many users participate in it and discuss the topic from different angles and perspectives. Therefore, at the same time point, hundreds or thousands of new messages may be generated. mutual influence

However, this phenomenon of multi-message propagation under the same topic has been largely ignored in previous studies

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