Research on the Computer Simulation Automation Process of News Communication Effect Under Big Data Environment

This paper proposes an automated evaluation system for news communication effect based on computer simulation, aiming to realize real-time analysis and optimization of news communication through big data technology. The system designs a communication effect evaluation model based on big data, combines the dynamic changes in the information dissemination process, and simulates the dissemination path and effect of different news content in different audience groups. The automated process is used to simulate the effect of news dissemination in multiple dimensions, and analyzes the impact of different dissemination strategies on audience participation, dissemination scope and information feedback. The simulation results are processed by data analysis tools to show the differences in the dissemination effects of different news content on various platforms, and provide quantitative evaluation indicators. The experimental results show that the evaluation system based on big data has significant advantages in improving the accuracy of news dissemination analysis. It can generate dissemination effect reports in real time and show data changes such as 30% increase in audience participation and 15% expansion of information dissemination scope under different strategies. This provides scientific decision-making support for news publishers and media managers.