Digital diplomacy and domestic audience: how official discourse shapes nationalist sentiments in China

China's significant investment in global outreach and influence, particularly through digital diplomacy, has become a crucial element of its public diplomacy strategy. This assertive diplomatic approach, often characterized by strong criticism of Western policies, is disseminated both internationally and domestically via Chinese media. While existing research focuses on the external impact of China's digital diplomacy, this study addresses the gap in understanding its domestic consequences, specifically concerning nationalist sentiments. The research question centers on how China's digital diplomatic discourse impacts domestic nationalist sentiments. This is important because understanding the domestic implications of China's foreign policy communication is vital for comprehending its overall strategy and potential effects on both internal and external relations. The study leverages Social Identity Theory (SIT) to examine the relationship between diplomatic discourse and two dimensions of nationalism: national identification and social derogation. The assertive nature of China's recent diplomacy has raised international concerns about rising nationalism, and the internet has become a key platform for its expression. However, most research focuses on high-profile international events, neglecting the daily expression of nationalist sentiments. This study aims to fill this gap by analyzing daily interactions between official discourse and public reactions.

The literature review explores existing scholarship on public diplomacy, digital diplomacy, and Chinese nationalism. Early definitions of public diplomacy focused solely on influencing foreign publics, but digital diplomacy has blurred the lines between domestic and foreign audiences. While numerous studies examine China's digital diplomacy's external impact, including its soft power projection and image cultivation, fewer studies investigate its domestic implications. Research on Chinese nationalism is categorized into top-down approaches, focusing on state-constructed narratives, and bottom-up approaches emphasizing spontaneous public expressions. The review notes the interplay between these approaches and the need to examine daily, rather than only event-driven, expressions of nationalism. This study seeks to bridge these gaps by examining the interplay between official diplomatic discourse on Bilibili, a major Chinese video platform with its unique bullet screen commenting system, and the resulting domestic nationalist sentiments. The study also acknowledges the need to analyze the various facets of Chinese diplomatic discourse, beyond solely focusing on the ‘wolf warrior’ diplomacy narrative.

This study employs a mixed-methods approach combining qualitative and quantitative techniques. Data were collected from videos of Chinese Ministry of Foreign Affairs (MFA) press conferences posted on Bilibili and the accompanying bullet screen comments. 200 videos, each with over 50,000 views and 100 bullet screen comments, were selected to ensure a representative sample across various time periods and diplomatic topics. The bullet screen comments were processed using Python and NLPIR, a Chinese word segmentation software, to identify keywords related to national identification and social derogation. Gooseeker, an automated coding instrument utilizing machine learning algorithms, was used to analyze the sentiment of the comments and categorize them based on pre-defined lexicons. The positivity of nationalist sentiments was measured using BosonNLP, the largest sentiment dictionary in China, which allowed the researchers to assess the sentiment score of bullet screens for each video. The tone of the spokespersons' remarks was coded as positive (1), negative (-1), or neutral (0), based on sentiment analysis using BosonNLP and the Chinese Diplomatic Language Corpus. The salience of the 'other' was categorized into three levels, with the United States (2), a second tier of countries including Australia, Canada, India, Japan, South Korea, and the United Kingdom (1), and other countries (0). A series of multivariate regression models with PROCESS were used to test the hypotheses, using ordinary least squares (OLS) regression with robust standard errors clustered by country. The study employed MacKinnon's four-step procedure to test mediation and used the Johnson-Neyman technique and plot conditional indirect effects to assess moderated mediation.

The findings support the hypothesis that positive official diplomatic discourse increases positive nationalist sentiments. This effect is primarily mediated by social derogation; negative discourse increases negative nationalism by heightening social derogation. While the mediating effect of national identification on positive nationalism was initially not significant, the moderated mediation analysis revealed that the salience of the 'other' significantly moderates both indirect effects. When facing more salient external others (e.g., the United States), the indirect effect through social derogation is stronger, leading to more negative sentiments. Conversely, the indirect effect through national identification is weaker when the 'other' is more salient, resulting in fewer positive sentiments. The study found a positive correlation between nationalism and official diplomatic discourse (r=0.21, p<0.01), and nationalism is positively correlated with national identification (r=0.58, p<0.001) but negatively correlated with social derogation (r=-0.71, p<0.001). The total effect of official diplomatic discourse on nationalism was significant (B=0.24, t=2.99, p<0.01). The indirect effect via social derogation was significant (indirect effect=0.16), while the indirect effect via national identification was insignificant without moderation. However, with the moderation of salience of other, both indirect effects were significantly moderated. The results indicated that when the external other is less salient, the indirect effect via national identification is stronger, leading to positive sentiments. Conversely, when the other is more salient, the indirect effect through social derogation is stronger. Alternative models testing simultaneous moderation of second-stage indirect effects and direct effects by salience of other were not supported.

The findings demonstrate that China's digital diplomatic discourse shapes domestic nationalist sentiments through a nuanced mechanism involving national identification and social derogation. The assertive diplomatic tone, while criticized internationally, is often received positively domestically, strengthening national identity and pride. The salience of the foreign 'other' plays a crucial role in influencing the direction and intensity of these sentiments. The study challenges the simplistic assumption that assertive diplomacy uniformly leads to negative nationalism, revealing a more complex relationship between official discourse, social identity processes, and public sentiment. This research highlights the crucial domestic dimension of digital diplomacy and adds a significant contribution to understanding Chinese nationalism and online communication.

This research contributes to understanding the domestic implications of China's digital diplomacy by demonstrating the influence of official diplomatic discourse on domestic nationalist sentiments. The study reveals a nuanced mechanism involving national identification and social derogation, moderated by the salience of foreign 'others.' Future research should incorporate socio-economic factors and employ more objective measurement techniques to further refine the understanding of this complex interplay. The study also highlights the importance of examining daily, rather than solely event-driven, expressions of nationalism in China.

The study acknowledges limitations related to data privacy preventing the inclusion of socio-economic background variables and the reliance on automated sentiment analysis, which might introduce subjective biases. Future research could address these limitations by incorporating more demographic data and employing more objective measurement techniques. The treatment of certain variables as ordinal while using them in continuous models might have reduced accuracy. Future studies should explore using categorical variable models.