Research on Cross-Cultural News Communication Modeling Method Driven by Multimodal Semantic Fusion

DOI

10.2991/978-2-38476-597-3_48How to use a DOI?

Keywords

Multimodal Semantic Fusion; Cross-Cultural News Communication; Cultural Context Perception; Communication Modeling; Deep Learning

Abstract

This paper proposes a cross-cultural news communication modeling method driven by multimodal semantic fusion. A cultural context-aware multimodal semantic fusion algorithm, CCAMF, is designed, and a cross-cultural news communication prediction model based on fusion communication dynamics is constructed. This method achieves deep collaborative expression of text and image information through three modules: hierarchical extraction of multimodal features, cultural context-aware semantic alignment, and residual-enhanced cross-modal fusion. It also combines cultural difference moderating factors and audience characteristics to jointly predict the scope, speed, and click-through rate. Experiments are conducted using both publicly available and self-built datasets for validation. Results show that the CCAMF semantic fusion accuracy reaches 89.7%, and the cross-cultural semantic alignment error is reduced to 0.078. The accuracy of the scope prediction reaches 88.2%, the MAE of the speed prediction is 0.082, and the F1 score of the click-through rate prediction reaches 87.6%. Ablation experiments further demonstrate that each core module has a significant effect on improving model performance. The research results show that this method can effectively improve the quality of multimodal semantic fusion and the accuracy of communication modeling in cross-cultural news scenarios, and has good stability, generalization, and application value.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Di Xiao
PY  - 2026
DA  - 2026/07/13
TI  - Research on Cross-Cultural News Communication Modeling Method Driven by Multimodal Semantic Fusion
BT  - Proceedings of the 4th International Conference on Language and Cultural Communication (ICLCC 2026)
PB  - Atlantis Press
SP  - 453
EP  - 459
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-597-3_48
DO  - 10.2991/978-2-38476-597-3_48
ID  - Xiao2026
ER  -