Optimal crisis management depends on how much the public can tolerate stringent measures. Using large-scale Weibo microblog data and two sentiment analysis models, this study investigated and compared public sentiment responses during the COVID-19 lockdowns in Wuhan and Shanghai, focusing on how residents’ emotional expressions evolved across different stages of the pandemic. Binary and six-emotion sentiment analysis models based on bidirectional encoder representations from transformers (BERT) were employed to examine how the two cities developed distinct emotional trajectories. Emotional responses in Wuhan followed emotional Phases of Disaster, with sharp transitions from shock to solidarity, followed by disillusionment. Conversely, Shanghai’s residents displayed stable emotional fluctuations with sustained management-oriented discourse. Word frequency analysis revealed that Wuhan citizens emphasized community self-help and mutual support, while Shanghai residents focused on systematic management processes, reflecting their approach to the crisis as an administrative challenge rather than an unprecedented disaster. These differences suggest that temporal positioning within the entire pandemic timeline fundamentally shapes how cities emotionally process extended health crises. In the early stage, the public responded primarily to the health threat itself, while in the later stage, they responded predominantly to the societal disruptions caused by containment policy. This study contributes to the crisis-management literature by providing methods to gauge public sentiment and demonstrating how temporal positioning influences public emotional responses during extended crises; and to the social-sensing literature by advancing methods for large-scale sentiment tracking.

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