The Social Mirror of Chinese AI: A Sentiment and Discourse Analysis of DeepSeek on Weibo
DOI:
https://doi.org/10.63313/SSH.9037Keywords:
Chinese AI, DeepSeek, Artificial Intelligence, LDA Topic Modeling, Sentiment Analysis, Techno-nationalism, Techno-optimismAbstract
As artificial intelligence (AI) becomes a defining force of the digital era, the rapid emergence of Chinese large language models has provoked widespread social reflection on technology, culture, and national identity. This study ex-plores how the Chinese public constructs emotional and cognitive under-standings of AI through discussions about DeepSeek, a large model developed in China. Based on 59,004 Weibo posts, the research applies Latent Dirichlet Allocation (LDA) topic modeling and sentiment analysis to investigate how users’ emotional attitudes and discursive orientations shape the social im-agination of Chinese AI.
The results identify three major discourse orientations: technological intima-cy, where users embed AI in daily routines and affective practices; tech-no-nationalism, where technology becomes a site of collective pride and na-tional autonomy; and techno-rationality, where participants engage in critical evaluation of transparency and performance. Although positive sentiments (46%) dominate the discourse, recurring concerns over data opacity and mod-el hallucination reveal persistent skepticism.
By drawing upon the concepts of sociotechnical imaginaries (Jasanoff & Kim, 2015) and mediated nationalism (Zhao, 2023), the study argues that DeepSeek embodies a new “social mirror” through which citizens negotiate meanings of progress, agency, and belonging. It contributes to global communication and AI studies by revealing how emerging technologies are emotionally inhabited and discursively localized within China’s mediated modernity.
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