Analysis of the innovation path of news dissemination based on the multivariate data chain network

Abstract

This paper explores the innovative path of news dissemination based on multivariate data chain network, through the design and implementation of a multivariate data chain integrated planning system, to improve the transmission efficiency and accessibility of the data chain network, and then optimize the effect of news dissemination. The study designs a multivariate data chain integrated planning system, considering the constraints of delay and transmission, and uses Poisson distribution and queuing theory to analyze the access delay of the data chain. It is found that the access delay can be effectively reduced by controlling the generation and transmission process of data packets. Secondly, the C-RTT algorithm is proposed to optimize the synchronous time slot allocation in Link16 network, which is experimentally demonstrated to improve the time slot utilization by 1.64% to 6.57% and significantly increase the network capacity. Further, the multivariate datalink dissemination model outperforms the traditional news dissemination method regarding news content perception, environmental awareness, news reliability, and environmental behavioral intention. The application of multivariate data chain network has significant advantages in news dissemination and has substantial impacts on the development of news industry.

Keywords

• multivariate data chain network
• c-rtt algorithm
• network capacity
• news dissemination
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