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Through the study, we identified four effective paths to improve governance performance and also found the key direction for future research on digital twin urban implementation of public crisis governance, i.e. how to find a balance between the cost and the effectiveness of governance.

A total of 22 urban public emergencies were selected based on key influencing factors, and four action paths to improve the performance of public crisis governance in digital twin cities were obtained using a fuzzy set qualitative comparative analysis model.

This paper identified digital twin technologies in urban public crisis governance, analyzed the key factors of public crisis governance in the digital twin city and proposed a path of action to improve the performance of public crisis governance in digital twin cities.

This study focuses on the influencing factors of public crisis governance in digital twin cities and the action paths to promote improved governance performance.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.