Emotional Evaluation of Digital Governance Technologies by Social Media Users: A Case Study of the Health Code

The Health Code represents a significant advancement in digital anti-epidemic efforts, with its technological dimension enhancing governance efficacy. It is essential to assess the perceived value for the target audience. This study focused on the Health Code, extracted Weibo posts from 2020 to 2022, employed Snow NLP and Baidu Senta for sentiment analysis, and implemented latent Dirichlet allocation topic modeling. The findings indicated that both public and official accounts exhibited a neutral to positively biased sentiment in public posts, with comments showing a positive correlation. The sentiment distribution in comments exhibited greater variability than that in posts. Regarding sentiment topics, popular discourse indicated support for the health-code system, whereas official discussions emphasized its rapid emergency roll-out. This study provides a research sample to elucidate the significance and value of digital governance technology in emergency management processes.