Abstract
This study explores how to use big data analysis technology to conduct a comprehensive, objective and in-depth assessment of the communication effect of China’s foreign discourse culture, with a view to optimizing the communication strategy and enhancing the effectiveness of international communication. This study systematically comprehends the theory of foreign discourse culture and soft power, the application of big data technology in the field of cultural communication, the current status of domestic and international research on the assessment of the communication effect of foreign discourse culture, as well as the construction of the theoretical framework for the assessment of the communication effect of foreign discourse culture based on big data and the setting of the research hypotheses. This study collects big data resources from various Internet media platforms such as social media, news media reports, international public opinion databases, online forums and blogs, and carries out data cleansing and standardization to lay a data foundation for the subsequent analysis. This study adopts two major data mining techniques, text mining and social network analysis, as well as a variety of data mining algorithms, such as topic modeling, sentiment analysis, and influence calculation, to conduct in-depth mining and analysis of the data on the cultural communication of foreign discourses, and develops a communication path recognition system for tracking and recording the trajectory of the dissemination of foreign discourses and constructing a communication network mapping. In addition, this paper demonstrates the effect of the model through specific cases. It is found that through the deep mining of big data, we can intuitively see the degree of influence of different discourse contents, communication channels, time nodes, and other factors on the communication effect, thus providing a scientific basis and decision-making support for policy makers and communication practitioners.
Get full access to this article
View all access options for this article.
