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In recent years, Chinese official media have accelerated their expansion on overseas communication platforms. Visual narratives targeting international audiences have increasingly become a crucial dimension in national image construction and discursive power competition. As a core narrative vehicle of China’s Global Development Initiative, the international communication effectiveness of the Belt and Road Initiative (BRI) directly concerns whether China’s proposals can be accurately understood and recognized worldwide. Meanwhile, image-text reporting is precisely the most intuitively persuasive media form in this regard. To this end, this study takes 64 image-text reports published between January 2025 and August 2026 in the BRI column of Xinhua News Agency’s English website as its research object. Adopting multimodal discourse analysis as the main analytical framework, it integrates Kress & van Leeuwen’s visual grammar theory with Martinec & Salway’s logico-semantic model of image-text relations. Starting from three types of image-text synergy patterns: reinforcing, complementary, and symbolic, it systematically examines their distribution characteristics, visual-verbal interaction patterns, and functions in national image construction. The findings reveal that the complementary pattern has the highest occurrence rate (87.5%), followed by the reinforcing pattern (68.8%), and the symbolic pattern the lowest (29.7%). The three patterns correspond respectively to three discursive strategies: “evidential visual argumentation,” “empathetic visual narrative,” and “metaphorical visual rhetoric,” serving three functions of national image construction: displaying hard power, communicating soft power, and fostering ideological identification. This study can provide a typological analytical approach for image-text research in international communication from the perspective of multimodal discourse analysis, offering empirical references for optimizing the overseas visual communication strategies of Chinese official media.
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Meiyu Chen (2026) studied this question.
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