An online social network information propagation analysis method based on time-varying damping motion

Abstract

The invention provides an online social network information propagation analysis method based on time-varying damping motion. The method comprises the following steps: S1, converting an online socialnetwork information propagation model into an information propagation time-varying model; S2, performing assignment display on parameters in the information propagation time-varying model; S3, randomly selecting one node in the online social information network with the node number of N as a seed node, injecting the information with the initial information energy of E into the seed node at the moment t = 0, diffusing and propagating on the network immediately, and counting the state of the social network; S4, collecting corresponding online social media propagation data, and comparing the online social media propagation data with the model simulation result data; And S5, sending a data result of one or any combination of the steps S1 to S4 to a remote terminal. The online social network information propagation analysis method can perform hot spot prediction on the online network event, and verifies the rationality and effectiveness of the prediction system through numerical analysis, simulation experiments and empirical data analysis.

Description

technical field [0001] The present invention relates to the technical field of online social information network, in particular to an online social network information dissemination analysis method based on time-varying damping motion. Background technique [0002] With the continuous development of mobile Internet technology and the advent of the 5G communication era, online social networks represented by Twitter, Facebook, and Weibo have developed rapidly, and have become important channels and carriers for social relationship maintenance and information dissemination in human society. The vigorous development of online social networks has greatly changed people's lifestyles on the one hand, from simple information search and web browsing to the construction and maintenance of online social relationships, information creation, communication and sharing based on social relationships; It has brought negative impacts to society, such as information dissemination, false inform...

AI Technical Summary

Problems solved by technology

It mainly includes network structure characteristics, information dissemination mechanism, group behavior evolution, etc., involving interdisciplinary research topics in computer science, sociology, communication, psychology, management, etc. Complexity, diverse user behaviors, massive and heterogeneous published information, and "big data" characteristics have resulted in traditional network evolution analysis methods being unable to meet the requirements, and there is an urgent need for new models and analysis methods for large-scale social networks

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