A Corpus-Based Study on China’s Image in the Foreign Ministry’s News Reports — A Case Study of Q&A in Regular Press Conferences

Abstract

This study investigates China’s national image constructed in the Q&A texts of regular press conferences hosted by the Ministry of Foreign Affairs (MOFA) of the People’s Republic of China. Focusing on addressing the imbalance where “external construction” of China’s image outweighs “self-construction” in existing research, it adopts a mixed-methods approach combining quantitative corpus analysis and qualitative discourse analysis based on Systemic Functional Grammar (SFG). A self-built corpus was constructed, comprising 5,486 Q&A exchanges from 577 regular press conferences held between 2023 and June 2025, sourced from the English website of MOFA. Using AntConc software, high-frequency words and their collocations were analyzed, revealing core terms such as “China,” “cooperation,” “peace,” “Taiwan,” and “sovereignty.” These terms reflect China’s emphasis on international engagement, commitment to peaceful development, and firm stance on safeguarding national sovereignty. Qualitative analysis, guided by SFG, further explored transitivity and modality systems. Material processes highlight China’s proactive role in global governance, while verbal processes emphasize its clear stance on international affairs. The strategic use of high-modal words for core interests and medium-low modal words for cooperative scenarios balances firmness and flexibility in diplomatic discourse. The findings indicate that MOFA press conferences construct a multidimensional Chinese image: resolutely safeguarding national sovereignty and territorial integrity; upholding international order as a responsible major power; advocating peace and cooperation; acting rationally, pragmatically, and trustworthy; and demonstrating confidence with global influence. This study enriches methodologies for national image research and provides practical insights for enhancing China’s international communication effectiveness.