Abstract

Traditional culture is a symbol of a country’s existence and history. The external dissemination of traditional culture is the key to expanding the country’s influence and enhancing the country’s international image. The external dissemination of culture also poses a potential impact on the country’s economy and development. In the context of the information age, the dissemination of Chinese traditional culture is attached great importance. The culture of the Forbidden City, from self-construction to borrowing, from online to offline all-media communication channels, unique and novel cultural and creative products and a young brand image provide it with a unique means of communication. The dissemination of the Forbidden City culture is of positive significance to the demonstration of cultural confidence and the innovation and development of culture, and it can be used as a typical case of the dissemination of Chinese traditional culture. Big data technology analyzes the research object through the process of data collection, data screening and data processing, combined with various data analysis tools, and the ultimate goal is to obtain favorable results for the analyst based on the analysis. The use of big data technology in cultural communication research has gradually become the focus of current scholars. This paper takes the Forbidden City culture as the research object, analyzes the current situation of the foreign communication of the traditional culture of the Forbidden City, puts forward the dilemma of the current external communication of Chinese traditional culture based on the current situation, summarizes the problems and reasons of traditional cultural communication, and designs corresponding solutions combined with big data technology. Through the data simulation of Chinese traditional cultural communication using big data solutions, it is found that the demand satisfaction, cultural benefits after cultural communication, and the direction of cultural influence have all improved after analyzing the user’s individual needs combined with big data technology.

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