Borders of belonging: how Chinese nationalism constructs exclusion in the age of populism

This paper investigates how state-led and popular nationalism in China construct borders as tools of exclusion, reinforcing national identity amidst global populist movements. Using the Belt and Road Initiative (BRI) as a case study, the analysis examines Global Times articles and corresponding user-generated content to reveal how geopolitical, ideological, and emotional borders are created and maintained through nationalist discourse. State-led nationalism emphasizes cooperation and diplomacy, framing borders to position China as a global leader promoting shared prosperity. In contrast, popular nationalism—expressed through user-generated comments—manifests in a confrontational, exclusionary discourse that delineates China from external adversaries, particularly Western powers. Through a mixed-methods approach—combining word frequency, sentiment, and emotional categorization using the NRC Emotion Lexicon—this study uncovers key differences between the two forms of nationalism. State narratives construct inclusive borders that foster international engagement, aligning with China’s diplomatic ambitions. Meanwhile, popular nationalism reflects heightened emotional intensity, especially through expressions of fear, anger, and opposition, creating rigid borders that emphasize ideological conflict and national pride. The research contributes to the literature on populism and border studies by demonstrating how Chinese nationalism functions as both a state strategy and a grassroots expression, delineating “the people” from “the other.” It highlights the critical role of media—both state-controlled outlets and user-generated platforms—in constructing and reinforcing these boundaries. As populism continues to shape political discourse globally, the study offers valuable insights into how nationalism in non-Western contexts mirrors broader populist strategies of identity formation through the construction of symbolic and emotional borders.