In recent years, vigorously developing the protection of intangible cultural heritage has become an important part of building a socialist culture with Chinese characteristics, shouldering the important task of promoting cultural exchanges and maintaining cultural diversity. Therefore, as an important object for the protection and inheritance of intangible cultural heritage, the study of English translation of folk literature has also received great attention from scholars. Protect and inherit folk literature, and improve the cultural soft power of certain regions of our country. Based on the big data, this article uses the early warning indicator system to protect and research the translation of non-heritage folk literature in my country and other tasks. Folk literature is our national treasure. It is very important to translate them into English, the most popular international language through the perspective of mesotranslatology. The English translation of intangible cultural heritage works of folk literature, as the carrier of China's excellent traditional culture, helps to promote the export process of the core values of socialism with Chinese characteristics, so that the essence of Chinese culture can be spread and popularized. The Chinese translation and literary circles have been committed to research in this field for a long time, aiming to let foreign readers understand the unique cultural and spiritual connotations of Chinese excellent folk literature. Enhance the cultural self-confidence of the people and the cultural strength of the country. The experimental research results show that, based on the perspective of mesotranslatology, the perspective of mesotranslatology plays a very important role in the translation of folk literature for some work in our country's folk literature translation.

Youya Zhou. English Translation of Intangible Heritage of Folk Literature from the Perspective of Medio-Translatology Based on Big Data. International Journal of Big Data Intelligent Technology (2022), Vol. 3, Issue 1: 9-16. https://doi.org/10.38007/IJBDIT.2022.030102.

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