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International Journal of Media and Communication Studies

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ArticleOpen Access http://dx.doi.org/10.26855/ijmcs.2025.12.005

Traffic Publicity Translation Empowered by Digital Intelligence and International Communication

Qiong Wu

School of Foreign Languages, East China Jiaotong University, Nanchang 330013, Jiangxi, China.

*Corresponding author: Qiong Wu

Published: December 2,2025

Abstract

Traffic publicity translation plays an important role in promoting exchanges and cooperation between different countries and regions. In the era of Artificial Intelligence, the application of digital intelligent technology in traffic publicity translation is increasingly prevalent, and its impact on international communication cannot be ignored. This article explores the relevant research, communication media, digital intelligence empowerment and translation principles of traffic publicity. With the help of digital intelligence technology represented by DeepL and ChatGPT, this paper analyzes the examples of traffic publicity translation, and reveals the strong potential of digital intelligence technology in empowering traffic publicity translation. The research finds that there are obvious advantages for digital intelligence technology represented by DeepL and ChatGPT when translating Chinese ordinary text into English, but when it comes to translating Chinese proper nouns, metaphor, nouns with cultural connotation, homophonic words, syntactic logical coherence, there is still a big gap in accuracy between artificial translation and human translation. The four principles of publicity translation play an important role in the post-translation editing of human translators. This research provides valuable insights for further exploring the impact of digital intelligent empowerment on traffic publicity translation and international communication.

Keywords

ChatGPT; DeepL; empowerment; traffic; publicity translation

References

Alves, F., & Albir, A. H. (2024). Translation as a cognitive activity: Theories, models and methods for empirical research. Routledge.

Chen, Z. (2021). Adaptation and alignment of Chinese and foreign cognitive styles in cross-cultural communication. Journal of Shandong Normal University (Social Sciences Edition), (1), 147-156.

Fu, J., & Yuan, L. (2022). Applied translation studies in my country under the new circumstances: Opportunities and challenges. Chinese Translation, (2), 97-102.

Geng, F., & Hu, J. (2023). A new direction for AI-assisted post-editing: A case study of translation based on ChatGPT. Foreign Languages in China, (3), 41-47.

Guan, X., & Lu, X. (2022). Corpus-based translation based on Python: Data analysis and theoretical exploration. Shanghai Jiao Tong University Press.

Huang, Y. (2004). Adhering to the principle of "three close connections" in foreign propaganda and properly handling the difficult issues in foreign propaganda translation. China Translation, (6), 27-28.

Kenny, D. (Ed.). (2017). Human issues in translation technology. Routledge.

Pym, A. (2023). Exploring translation theories (3rd ed.). Routledge.Chen, X. (2013). Cultural awareness and audience consciousness in translation for external communication. Chinese Translation, (2), 95-100.

Sun, Y., & Zhou, T. (2024). A glimpse into the English translation of metaphors from the perspective of national translation practice. Contemporary Foreign Language Studies, (1), 125-135.

Wen, X., & Tian, Y. (2024). A study on the effectiveness of ChatGPT in the translation of discourses with Chinese characteristics. Shanghai Translation, (2), 27-34.

Wu, Y., & Sun, M. (2023). Audience concepts and behavioral mechanisms in translation for foreign languages. Journal of Shanghai Jiao Tong University (Philosophy and Social Sciences Edition), (8), 61-72.

Yuan, X. (2005). Strategies and rationale for English translation of foreign propaganda. Chinese Translation, (1), 75-78.

Zeng, J. (2018). Chinese characteristics and discourse integration in translation for foreign publicity. Jiangxi Social Sciences, (10), 239-245.

Zhan, X., Li, B., & Sun, J. (2023). Scenario-based application and development opportunities of AIGC in the context of digital intelligence integration. Library and Information Knowledge, (1), 75-85.

How to cite this paper

Traffic Publicity Translation Empowered by Digital Intelligence and International Communication

How to cite this paper: Qiong Wu. (2025). Traffic Publicity Translation Empowered by Digital Intelligence and International Communication. International Journal of Media and Communication Studies1(1), 24-32.

DOI: http://dx.doi.org/10.26855/ijmcs.2025.12.005