A Model for Evaluating the Effectiveness of News Dissemination under the Combination of Big Data and Artificial Intelligence

In today's era of information explosion, with the rapid development of big data technology and artificial intelligence, the form of news dissemination and the assessment mode of dissemination effect are undergoing profound changes. The traditional method of evaluating the effect of news dissemination relies on limited indicators and a single data source, which is difficult to accurately reflect the multidimensional response of the audience and its dissemination path in modern news dissemination. In contrast, this paper proposes a new news communication effect assessment model by combining big data analysis and artificial intelligence algorithms, which can effectively process massive data, deeply explore the audience's behavioral characteristics, emotional changes and information dissemination path, and then provide a more accurate assessment of the communication effect. Although AI reduces the demand for labor in conventional occupations, it increases the demand for labor in non-conventional occupations, which mainly comes from the increase in the demand for non-conventional cognitive occupations such as management and technology. The job creation effect of AI is not only reflected in the connotation, i.e., the increase in the number of demand for the labor force of the already existing non-conventional occupations. The results of the study show that the deep combination of big data and artificial intelligence not only significantly improves the depth and breadth of the analysis of news communication effects, but also provides a more intelligent and automated solution for the future evaluation of communication effects.